System, method, software architecture, and business model for an intelligent object based information technology platform

ABSTRACT

In one aspect, the invention provides an architecture and query and processing methodology, advantageously implemented in software, for an information technology platform using Intelligent Molecular Objects or objects of a more general character. In another aspect, it provides intelligent molecular object data or other data for heterogeneous data environments with high data density and dynamic application needs. In yet another, it provides an Object State Engine for intelligent molecular object data technology. In still another, it provides an Object Translation Engine for intelligent molecular object data in heterogeneous data environments with dynamic application needs. In yet another aspect, it provides a handling device including an Intelligent Object Handler for intelligent molecular object data in heterogeneous data environments with high data density and dynamic application needs. In even still another aspect, the invention provides a data pool architecture and an Intelligent Object Pool for intelligent molecular object data in heterogeneous data environments with high data density and dynamic application needs. An architecture for an information technology platform using Intelligent Molecular Object software is provided, which addresses all steps of data processing from data acquisition through diverse sources and instrumentation to final output of diverse data analysis results.

RELATED APPLICATIONS

[0001] Priority is hereby claimed under 35 U.S.C. 120 and/or 35 U.S.C.119(e) to the following United States Provisional and Utility PatentApplications, each of which is hereby incorporated by reference:

[0002] U.S. Utility patent application Ser. No. ______ (Attorney DocketNo. A-70134/RMA) filed Dec. 06, 2001 and entitled Data PoolArchitecture, System, And Method For Intelligent Object Data InHeterogeneous Data Environments;

[0003] U.S. Utility patent application Ser. No. ______ (Attorney DocketNo. A-70135/RMA) filed Dec. 06, 2001 and entitled Intelligent MolecularObject Data Structure and Method for Application in Heterogeneous DataEnvironments with High Data Density and Dynamic Application Needs;

[0004] U.S. Utility patent application Ser. No. ______ (Attorney DocketNo. A-70136/RMA) filed Dec. 06 2001 and entitled Intelligent ObjectHandling Device and Method for Intelligent Object Data in HeterogeneousData Environments with High Data Density and Dynamic Application Needs;

[0005] U.S. Utility patent application Ser. No. ______ (Attorney DocketNo. A-70310/RMA) filed Dec. 6, 2001 and entitled System, Method,Software Architecture, And Business Model For An Intelligent ObjectBased Information Technology Platform;

[0006] U.S. Provisional Application Serial No. 60/254,063 filed Dec. 6,2001 entitled Data Pool Architecture for Intelligent Molecular ObjectData in Heterogeneous Data Environments with High Data Density andDynamic Application Needs;

[0007] U.S. Provisional Application Serial No. 60/254,062 filed Dec. 6,2001 entitled Intelligent Molecular Object Data for Heterogeneous DataEnvironments with High Data Density and Dynamic Application Needs;

[0008] U.S. Provisional Application Serial No. 60/254,064 filed Dec. 6,2001 entitled Handling Device for Intelligent Molecular Object Data inHeterogeneous Data Environments with High Data Density and DynamicApplication Needs;

[0009] U.S. Provisional Application Serial No. 60/259,050 filed Dec. 29,2001 entitled Object State Engine for Intelligent Molecular Object DataTechnology;

[0010] U.S. Provisional Application Serial No. 60/264,238 filed Jan. 25,2001 entitled Object Translation Engine Interface For IntelligentMolecular Object Data;

[0011] U.S. Provisional Application Serial No. 60/266,957 filed Feb. 6,2001 entitled System, Method, Software Architecture and Business Modelfor an Intelligent Molecular Object Based Information TechnologyPlatform;

[0012] U.S. Provisional Application Serial No. 60/276,711 filed Mar. 16,2001 entitled Application Translation Interface For IntelligentMolecular Object Data In Heterogeneous Data Environments With DynamicApplication Needs;

[0013] U.S. Provisional Application Serial No. 60/282,656 filed Apr. 9,2001 entitled Result Generation Interface For Intelligent MolecularObject Data In Heterogeneous Data Environments With Dynamic ApplicationNeeds;

[0014] U.S. Provisional Application Serial No. 60/282,658 filed Apr. 9,2001 entitled Knowledge Extraction Engine For Intelligent Object Data InHeterogeneous Data Environments With Dynamic Application Needs;

[0015] U.S. Provisional Application Serial No. 60/282,654 filed Apr. 92001 entitled Result Aggregation Engine For Intelligent Object Data InHeterogeneous Data Environments With Dynamic Application Needs;

[0016] U.S. Provisional Application Serial No. 60/282,657 filed Apr. 9,2001 entitled Automated Applications Assembly Within Intelligent ObjectData Architecture For Heterogeneous Data Environments With DynamicApplication Needs;

[0017] U.S. Provisional Application Serial No. 60/282,655 filed Apr. 9,2001 entitled System, Method And Business Model For Productivity InHeterogeneous Data Environments;

[0018] U.S. Provisional Application Serial No. 60/282,979 filed Apr. 10,2001 entitled Legacy Synchronization Interface For Intelligent MolecularObject Data In Heterogeneous Data Environments With Dynamic ApplicationNeeds;

[0019] U.S. Provisional Application Serial No. 60/282,989 filed Apr. 10,2001 entitled Object Query Interface For Intelligent Molecular ObjectData In Heterogeneous Data Environments With Dynamic Application Needs;

[0020] U.S. Provisional Application Serial No. 60/282,991 filed Apr. 10,2001 entitled Distributed Learning Engine For Intelligent MolecularObject Data In Heterogeneous Data Environments With Dynamic ApplicationNeeds; and

[0021] U.S. Provisional Application Serial No. 60/282,990 filed Apr. 10,2001 entitled Object Normalization For Intelligent Molecular Object DataIn Heterogeneous Data Environments With Dynamic Application Needs;

[0022] each of which U.S. utility and U.S. provisional patentapplication is hereby incorporated by reference in its entirety.

FIELD OF INVENTION

[0023] This invention pertains generally to system, method, computerprogram product, data structure and architecture, data management, andsoftware architecture; and more particularly to system, method, computerprogram product, and data structure and architecture, data management,and software architecture in the life sciences, biotechnology,therapeutic diagnostic and intervention, pharmaceuticals, andbioinformatics.

BACKGROUND

[0024] As demand for Information Technology (IT) software and hardwareto provide global data access and integrated business solutions hasexploded, significant challenges have become evident. A central problemposes access, integration, and utilization of large amounts of new andvaluable information generated in each of the major industries. Lack ofunified, global, real-time data access and analysis is detrimental tocrucial business processes, which include new product discovery, productdevelopment, decision-making, product testing and validation, andproduct time-to-market.

[0025] With the completion of the sequence of the human genome and thecontinued effort in understanding protein expression in the lifesciences, a wealth of new genes are being discovered that will havepotential as targets for therapeutic intervention. As a result of thisnew information, however, Biotech and Pharmaceutical companies aredrowning in a flood of data. In the Life Sciences alone, approximately 1Terabyte of data is generated per company and day, of which currentlythe vast majority is unutilized for several reasons.

[0026] First, data are contained in diversified system environmentsusing different formats, heterogeneous databases and have been analyzedusing different applications. These applications may each applydifferent processing to those data. Competitive software, based onproprietary platforms for network and applications analysis, haveutilized data platform technologies such as SQL with open databaseconnectivity (ODBC), component object model (COM), Object Linking andEmbedding (OLE) and/or proprietary applications for analysis asevidenced in patents from such companies as Sybase, Kodak, IBM, andCellomics in U.S. Pat. Nos. 6,161,148, 6,132,969, 5,989,835, 5,784,294,for data management and analysis, each of which patents are herebyincorporated by reference. Because of this diversity, despite the fact,that the seamless integration of public, legacy and new data is crucialto efficient drug discovery and life science research, current datamining tools cannot handle all data simultaneously. There is asignificant lack of data handling methods, which can utilize these datain a secure, manageable way. The shortcomings of these technologies areevident within heterogeneous software and hardware environments withglobal data resources. Despite the fact that the seamless integration ofpublic, legacy and new data is crucial to efficient research(particularly in the life sciences), product discovery (such as forexample drug, or treatment regime discovery) and distribution, currentdata mining tools cannot handle or validate all diverse datasimultaneously.

[0027] Second, with the expansion of high numbers of dense data in aglobal environment, user queries often require costly massive parallelor other supercomputer-oriented processing in the form of mainframecomputers and/or cluster servers with various types of networkintegration software pieced together for translation and accessfunctionality as evidenced by such companies as NetGenics, IBM andChannelPoint in U.S. Pat. Nos. 6,125,383 6,078,924, 6,141,660,6,148,298, each of which patents are herein incorporated byreference—(e.g. Java, CORBA, “wrapping”, XML) and networkedsupercomputing hardware as evidenced by such companies as IBM, Compaqand others in patents such as for example U.S. Pat. Nos. 6,041,398,5,842,031, each of which is hereby incorporated by reference. Even withthese expensive software and hardware infrastructures, significanttime-delays in result generation remain the norm.

[0028] Third, in part due to the flood of data and for other reasons aswell, there is a significant redundancy within the data, making queriesmore time consuming and less efficient in their results.

[0029] Fourth, an additional consideration, which is prohibitive tochange towards a more homogenous infrastructure, is cost. The cost tobring legacy systems up to date, to retool a company's Intranet basedsoftware systems, to carry out analysis with existing tools, or even toadd new applications can be very expensive. Conventional practicesrequire retooling and/or translating at application and hardware layers,as evidenced by such companies as Unisys and IBM in U.S. Pat Nos.6,038,393, 5,634,015.

[0030] Because of the constraints outlined above, it is nearlyimpossible to extract useful, relevant information from the entity ofdata within reasonable computing time and efforts. For this reason, thedevelopment of architecture to overcome these obstacles is needed.

[0031] These are not the only limitations. With the advent of distinctdifferentiations in the field of genomics, proteomics, bioinformaticsand the need for informed decision making in the life sciences, thestate of object data is crucial for their overall validation and weightin complex, multi-disciplinary queries. This is even more important dueto inter-dependencies of a variety of data at different states.Furthermore, because biological data describe a “snapshot” of complexprocesses at a defined state of the organism, data obtained at any timerefer to this unique phase of metabolism. In order to account formeaningful comparison, thus, only data in similar states can beutilized. Therefore, there is a growing need for a object data stateprocessing engine, which allows to continuously monitor, govern,validate and update the data state based on any activities ofintelligent molecular objects in real-time.

[0032] Data translation processes between different data types aretime-consuming and require provision of information on data structureand dependencies, in spite of advances in information technology. Theseprocesses, although available and used, have a number of shortcomings.Data contained in diversified system environments may use differentformats, heterogeneous databases and different applications, each ofwhich may apply different processing to those data. Because of that,despite the fact that the seamless integration of public, legacy and newdata is crucial to efficient drug discovery and life science research,several different applications and/or components have to be designed inorder to translate each of those data sets correctly. These requiresignificant effort and resources in both, software development and dataprocessing. With the advent of distinct differentiations in the field ofgenomics, proteomics, bioinformatics and the need for informed decisionmaking in the life sciences, access to all data is crucial for overallvalidation and weight in complex, multi-disciplinary queries. This iseven more important due to inter-dependencies of a variety of data atdifferent states. The current individual data translation approach doesnot support these needs. Because biological data describe a “snapshot”of complex processes at a defined state of the organism, data obtainedat any time refer to this unique phase of metabolism. In order toaccount for meaningful comparison, thus, only data in similar states canbe utilized. The latter requires real-time processing and automated,instant data translation of data from different sources. Therefore,there is a growing need for an object data translation engine, whichallows for bi-directional translation of multidimensional data fromvarious sources into intelligent molecular objects in real-time.

[0033] The flood of new and legacy data results in a significantredundancy within the data making queries more time consuming and lessefficient in their results. There is a lack of defined sets of userinteraction and environment definition protocols, which are needed toprovide means for intelligent data mining and optimization in resultvalidation towards real solutions and answers. An additionalconsideration, which is prohibitive to change towards a more homogeneousinfrastructure is the missing of object representation definitionprotocols to prepare and present data objects for interaction withinheterogeneous environments. Lastly, data currently are interacted withand presented in diverse user interfaces with dedicated, unique featuresand protocols preventing universal, unified user access. Thus, ahomogeneous, unified presentation such as a web-enabled graphical userinterface which integrates components from diverse applications andlaboratory systems environments is highly desirable, but currentlynon-existent for objects in real-time.

[0034] Because of these constraints, it is nearly impossible to extractuseful, relevant information from the entity of data within reasonablecomputing time and efforts. For this reason, the development of anarchitecture and unifying user interface to overcome these obstacles isneeded.

[0035] Relevant Patents

[0036] U.S. Pat. Nos. 6,136,274, 6,125,383, 6,052,722, 6,016,495,5,937,189, 5,596,744, 5,867,799, 5,745,895, 6,076,088, 5,706,453,5,767,854, 6,035,300, 6,145,009, 5,974,532, 5,873,097, 6,094,656,6,136,274, 6,138,171, 6,144,989, 6,137,499, 6,016,393. 6,145,009,6,167,563, 6,144,989, 6,134,664, 6,125,383, 6,111,893, 6,108,661,6,102,969, 6,078,924, 6,076,088, 5,964,891, 5,937,189, 5,745,895,5,664,215, 6,052,722, 6,064,382, 6,134,581, 6,146,027, 5,664,066,5,862,325, 6,016,495, 6,119,126.

[0037] Relevant Literature:

[0038] Elisa Bertino, Susan Urban, Elke A. Rundensteiner (eds.): Theoryand Practice of Object Systems (1999) 5 (3): 125-197; Akmal B. Chaudhri,Julie A. McCann, Peter Osmon: Theory and Practice of Object Systems(1999) 5 (4): 263-279; D. Cai, M. F. McTear, S. I. McClean InternationalJournal of Intelligent Systems (2000): 15 (8): 745-761; Carol A. Hert,Elin K. Jacob, Patrick Dawson: Journal of the American Society forInformation Science (2000) 51 (11): 971-988. F. J. González-Castaño, L.Anido-Rifón, J. M. Pousada-Carballo, P. S. Rodríguez-Hernández, R.López-Góm: Software: Practice and Experience (2001) 31 (1): 1-16; DanielE. Cooke, Per Andersen: Software: Practice and Experience (2000) 30(14): 1541-1570; Akmal B. Chaudhri: Theory and Practice of ObjectSystems (1999) 5 (4): 199-200; Lee A. Segel: Complexity (2000) 5 (6):39-46; L. J. G. T. van Hemmen: International Journal of NetworkManagement (2000) 10 (6): 261-275. Joel E. Henry: Journal of SoftwareMaintenance: Research and Practice (2000) 12 (4): 229-248; MichaelMattsson, Jan Bosch: Journal of Software Maintenance: Research andPractice (2000) 12 (4): 79-102; Sally Mcclean, Bryan Scotney, MaryShapcott: International Journal of Intelligent Systems (2000) 15 (6):535-547; Julie M. Hurd: Journal of the American Society for InformationScience (2000) 51(14): 1279-1283; Serge Demeyer, Matthias Rieger, TheoDirk Meijler, Edzard Gelsema: Theory and Practice of Object Systems(1999) 5 (2): 73-81; Dao et al: IEEE (1991): 88-91. Joel E. Henry:Journal of Software Maintenance: Research and Practice (2000) 12 (4):229-248; Michael Mattsson, Jan Bosch: Journal of Software Maintenance:Research and Practice (2000) 12 (4): 79-102; Sally Mcclean, BryanScotney, Mary Shapcott: International Journal of Intelligent Systems(2000) 15 (6): 535-547; Julie M. Hurd: Journal of the American Societyfor Information Science (2000) 51 (14): 1279-1283; Serge Demeyer,Matthias Rieger, Theo Dirk Meijler, Edzard Gelsema: Theory and Practiceof Object Systems (1999) 5 (2): 73-81. Mark Baker: Software Focus:Parallel programming with Java (2000) 1 (1); C. N. Lauro, G. Giordano,R. Verde: Applied Stochastic Models and Data Analysis: Amultidimensional approach to conjoint analysis (1998) 14 (4): 265-274;P. America: Formal Aspects of Computing: Issues in the Design of aParallel Object-Oriented Language [POOL] (1989) 1 (4): 366-411.

SUMMARY

[0039] The invention has numerous aspects. In one aspect, the inventionprovides an architecture and query and processing methodology,advantageously implemented in software, for an information technologyplatform using Intelligent Molecular Objects (IMO). In another aspect,the invention provides intelligent molecular object (IMO) data forheterogeneous data environments with high data density and dynamicapplication needs. In yet another aspect, the invention provides anObject State Engine (OSE) for intelligent molecular object datatechnology. In still another aspect, the invention provides an ObjectTranslation Engine (OTE) for intelligent molecular object data inheterogeneous data environments with dynamic application needs. In yetanother aspect, the invention provides a handling device including anIntelligent Object Handler (IOH) for intelligent molecular object datain heterogeneous data environments with high data density and dynamicapplication needs. In even still another aspect, the invention providesa data pool architecture and an Intelligent Object Pool (IOP) forintelligent molecular object data in heterogeneous data environmentswith high data density and dynamic application needs. These and otheraspects are described in greater detail below as well as in the detaileddescription hereinafter relative to the figures.

[0040] A software architecture for an information technology platformusing “Intelligent Molecular Object” (IMO™) software is provided, whichaddresses all steps of data processing from data acquisition throughdiverse sources and instrumentation to final output of diverse dataanalysis results. The architecture's data elements are uniquely defineddata objects, Intelligent Molecular Objects (IMOs), consisting of setsof functional property pane layers, activated or disabled via a propertypane controller. Each IMO contains a unique identifier for object dataaccess and security, and property pane layers defining the origin of theobject and routing content and results interactively across the network.Status management components on the object level provide real-timecontrol of object activity, activity records logging, data integritymonitoring, state management for network object data, GLP/GMP compliantstate assignment and information request ranking. Status managementprocessing engines also handle external query submission and resultsynchronization for inter-object queries, allowing the IMOs tocommunicate intelligently via vectorized, direct addressing of datasubsets, and keeping track of their interactions. Meta-data indices,workspace-oriented vector subsets and object pane descriptors allow forfast, direct communication with diversified applications and databasesvia an object query interface and integrated application translatorlinks. Processing engines are included to standardize and/or normalizedata from diverse sources, providing a means to accurately compare data,to test for identity, for increase or decrease in values or functionalrelevancy. In particular, algorithms for tracking and normalization ofobject or image data are provided which allow to extract variable andnon-variable regions within sets of data and generate a global standardto which all data can be referred. By applying these algorithms,adjustments to all necessary parameters in a multidimensional data setcan be made automatically and simultaneously. In addition, functionalityis provided for direct information interchange between objects,graphical preview of the object data, raw data matrix structuredescriptions, and the like.

[0041] Further described is an applications framework within the IMOtechnology, called “Intelligent Object Handler” (IOH), which providessets of user interactions and object environment definition protocols.The described IOH is comprised of sets of processing engines and accessinterfaces, which prepare and present IMO data objects for interactionwithin heterogeneous environments. A unified presentation layer withinthe IOH provides a web-enabled graphical user interface, whichintegrates components or modules from diverse applications andlaboratory systems environments, and acts as a handler for IMO data.Additional IOH components include a user definition administrationshell, a master query component and an interface to automate the queryof application and database requirements. The creation and initiation ofnew IMOs is provided via an integrated IMO generator. A directinstrument acquisition and control interface and a component forautomated application assembly provide integration of real-time dataacquisition and analysis. Data type translators are provided to automatetransformation from heterogeneous data sources into IMO data inreal-time. Automated normalization of data, by calibration withempirical criteria within the workspace standardization techniquereferred to above, is managed through pointers to meta-data tags andvector subsets. An integrated object translation engine processesinteractions such as transformation, integration and information accessbetween intelligent object data and other data environments to enablereal-time communication. These processes automatically determine otherdata structures, look up functional information of the data, createdescriptors which correspond to object property pane layers anddetermine application type and access to IMOs in real-time. Analyticalfunctionality is provided by access interfaces and processing enginesintegrated at the IOH level. These engines and interfaces provide secureaccess to multidimensional queries across heterogeneous environments andsynchronization with offline legacy systems. Real-time result generationand engines for distributed learning and knowledge extraction alsoreside within the IOH.

[0042] The IMO IT architecture provides also processes, which define andgovern a global virtual data pool, the “Intelligent Object Pool” (IOP).These processes contain definitions for subsets, called Intra-Pools(iPools), which are regulated by pool boundary protocols. iPool securityauthentication, availability monitoring, object persistence andintegrity assessment components are provided. Interfaces for meta-dataqueries are integrated within the IOP, such as interactive presortingand exclusion algorithms, object clustering and object-to-objectinteraction rules. Content access definitions such as object-to-analysistools interactions, result merging algorithms and a real-time answergenerator are also integrated at the IOP level. Rapid, relevant dataaccess is enabled through object-to-object and iPool-to-iPool meta-dataindexed access, and iPool integrity assessment. Additionally, poolcontent access protocols and order definitions allow for objectproperty-selective pre-sorting, real-time result aggregation andreal-time exclusion of irrelevant object data layers. Other componentsinclude pool exchange protocols, real-time meta-data links and indexing,queries across pools and several tools for meta-data index andsignificance aggregation in real-time. Functions are also provided todefine the proximity of individual IMO data within the IOP. Thus, theIOP provides an engine for global result aggregation across diversifieddata subsets.

[0043] Methods are provided for: object data creation andidentification; root data and meta-data content routing; data statusmanagement; meta-data indexing; and object query and response managementfor diversified data in networked Life Sciences applicationsenvironments. Intelligent Molecular Object (IMO) technology improvesdata usability and rate of access to query-relevant elements, attributesand other “meta-data” (data about the data). The technology providesreal-time access to previously unusable data and significantly reducesresponse time for queries of large datasets. The technology providesdata management and access across hardware and software platforms andresearch applications. The technology secures data for global networkuse and exchange, and provides extensible options, including ownershipmanagement, data integrity, use-tracking, and selective access. Dataobject handling and storage technology for customization, analysis, andexchange is provided.

[0044] Methods and functions are provided for: a continuously-running(always-on) set of processes, which comprise an intelligent object stateengine to monitor and govern activities of intelligent molecular objectsin real-time, including a component to trigger the creation of a newobject and assign a unique identifier to it; a component, which monitorsany object activity or transaction with the object and records itsactivity history; a component, which relates activities toGLP/GMP-compliant data states and assigns a defined state to the objectto validate the current action; a component, which governs access to theobject and object-to-object activities based on security protocols andprivilege definitions; a status memory for state-less networks, whichtransmits action consequences back to the backend system; a validationstate based information exchange ranking component; a state-relatedvector definition of object data subsets for dynamic informationinterchange; and, a query processing component for handling externalquery submissions to the object and object-to-object query resultsynchronization.

[0045] Methods and functions are provided for sets of event-drivenprocesses, which comprise an intelligent real-time translation enginefor integration of intelligent molecular objects within heterogeneousdata environments with dynamic application needs. The methods andfunctions include: a component which carries out data table extractionto determine data object, data field and raw data matrix definitions forintelligent molecular objects; a component which provides data object,data field and raw data matrix structure definition tables forintelligent molecular objects; a component which provides data structureinformation for standardization of non-object data; a component whichcarries out data type extraction to determine data access and structuredependencies for intelligent molecular objects; a component whichprovides data type, access and structure definition tables forintelligent molecular objects; a component which carries out databasetype extraction to determine database access and structure dependenciesfor intelligent molecular objects; a component which provides databasetype, access and structure definition tables for intelligent molecularobjects; a component which carries out application type extraction todetermine application type, access and structure for intelligentmolecular objects; a component which, provides application type, accessand structure definition tables for intelligent molecular objects; acomponent which provides table lookup to provide real-time translationof the intelligent molecular object within heterogeneous database andapplication environments; and, a component to provide intelligentmolecular object pane presentation in real-time, according to defineddata structure, database, and application requirements.

[0046] Methods are provided for: unified presentation and management ofuser definition, administration and security protocols; definition ofuser interaction and computing environment protocols; and definition ofdata type translation protocols. Additional methods are provided for:real-time generation of Intelligent Molecular Object (IMO) data; dataobject standardization; and definition of object representation forunified data acquisition, management and analysis in heterogeneous dataenvironments with high data density and dynamic application needs. TheIntelligent Object Handler (IOH) technology presents a unified andweb-enabled user environment which fields queries and commands andpresents significant analytical results in real-time via meta-dataprotocols. The technology described automates data acquisition andtransformation from heterogeneous data sources and/or types to anempirically normalized, meta-data indexed Intelligent Molecular Object(IMO) data standard. The technology described herein makes diverse dataaccessible to analysis by heterogeneous application types, providing asecured, unified, web-enabled environment for real-time, integratedacquisition and analysis of previously heterogeneous data.

[0047] Methods are provided for a meta-data enhanced storage andanalytical resource for Intelligent Molecular Object (IMO) data. TheData Pool Architecture defined herein enables Intelligent MolecularObjects to communicate via active object algorithms. The technologydefined herein provides boundary protocols for secure integration andaccess to global and/or local data pools; and content access definitionsfor real-time significance detection and results generation. Thetechnology defined herein provides automated meta-data indexing andobject-to-object query result aggregation for real-time answers toqueries within heterogeneous data environments with high data densityand dynamic application needs.

BRIEF DESCRIPTION OF THE FIGURES

[0048]FIG. 1 is a representation of the general IMO IT architecture,depicting relationships between framework, engines, interfaces and othercomponents.

[0049]FIG. 2 is a representation of functional relationships betweeninstruments, applications and diverse databases within the IMOarchitecture.

[0050]FIG. 3 is a representation of a multi-user network collaborativeresearch.

[0051]FIG. 4 is a representation of a flow chart of typical dataprocessing within the IMO IT architecture.

[0052]FIG. 5 is a representation of the user interface of an intelligentmolecular object (IMO) showing its unique identifier pane (UID).

[0053]FIG. 6 is a representation of the user interface of an intelligentmolecular object (IMO) showing its status management component (objectstate engine, OSE).

[0054]FIG. 7 is a representation of the user interface of an intelligentmolecular object (IMO) showing the optional object graph preview (OGP)pane comprising a limited resolution image/graphics viewer.

[0055]FIG. 8 is a representation of a flow chart depicting processes ofthe object state engine.

[0056]FIG. 9 is an example list of common state designations for lifescience applications.

[0057]FIG. 10 is an example of an object state history, comprised oftime-sequential set of object activity records (OAR).

[0058]FIG. 11 is a representation of the unified presentation ofheterogeneous data within a query.

[0059]FIG. 12 depicts the unified data presentation processing throughthe object translation engine for real-time analysis access.

[0060]FIG. 13 is a representation of the unified graphical userinterface for IMO technology.

[0061]FIG. 14 is a representation of a query dialog utilizing the IMOdata handling features.

[0062]FIG. 15 depicts a representation of the process model for theintelligent molecular object pool(IOP).

[0063]FIG. 16 depicts a chart representation of intra-pool (iPool)relationships and intelligent molecular object (IMO) relationshipswithin the iPool.

[0064]FIG. 17 depicts a GUI screen representation within the unifiedpresentation layer (UPL) concept, showing a graphical view of objectintra-pools and their data subsets and a dendrogram representation ofdependencies and similarities of object properties based on meta-dataindexed results.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

[0065] The inventive Intelligent Molecular Object Information Technology(IMO IT) Platform and its constituent subsystems, methods, procedures,and computer software algorithms, solves the diversified data and formatas well as the heterogeneous database and applications problems byintegrating unique components, processes, engines and interfaces such asnetworked data type, database, and application type detection and tablegeneration, coupled with multidimensional table lookup and pointers.These components, processes, engines and interfaces work within the IMOIT architecture at the data object level to provide such advantages asautomated, real-time access, and translation capabilities, thus enablinginstant handling of diverse data in heterogeneous applicationsenvironments.

[0066] The IMO IT Platform also solves these and other problems andlimitations of conventional systems and methods by integrating uniquecomponents, processes, engines and interfaces such as workspace vectorsubset selection, dynamic meta-data indexing at the data object and datasubset levels, as well as direct information interchange at the dataobject and data subset levels. These components, processes, engines andinterfaces, work within the IMO IT architecture to provide significantadvantages for efficient analysis of high numbers of high density data,allowing for true real-time data acquisition and analysis in a globaldata environment.

[0067] The IMO IT Platform technology, in contrast to conventionalexisting technologies described in the background, does not reproduce oralter the raw data in any way, thus eliminating data redundancy whilesimultaneously enabling multiple queries on a single data objectsimultaneously. By using meta-data reference tables, pointers and tagsto provide real-time translation and integration, which efficientlyrefers only to the aspects of any raw data relevant to a specific query,the IMO IT Platform avoids data redundancy and data access lockingrequirements. This provides significant advantages over currentlyexisting technologies as described by such companies as Oracle andSybase, for example, in U.S. Pat. Nos. 6,105,030; 5,832,484; each ofwhich is hereby incorporated by reference.

[0068] Furthermore, in contrast to the conventional practices requiringretooling and/or translating at application and hardware layers,described in the Background, the IMO IT Platform enables translation,applications integration and validation of existing systems, inreal-time, at the data object level. This allows for efficientscalability, interoperability and applications development withoutretooling existing systems, and provides for data-enabled validation ofexisting hardware and software systems.

[0069] In one aspect, the inventive methods and procedures remedy theseconstraints and limitations by providing an architecture allowinginteractive, object-based intelligent communication in-between the dataitself to extract all relevant content in a fast, unique and automatedmanner, within complex network environments without the need ofupgrading or replacing current computer systems.

[0070] These methods and procedures, also remedy these constraints andlimitations by allowing interactive, object-based intelligentcommunication in-between the data itself to extract all relevant contentin a fast, unique and automated manner, within complex networkenvironments without the need of upgrading or replacing current computersystems. The intelligent molecular object technology provides a flexibleglobal standard, which allows for seamless integration and real-timeanswers to complex, multidimensional and interdependent queries. Theintelligent molecular object technology provides a framework forscale-up and dynamically changing application needs in bioinformaticsand the life sciences.

[0071] They also remedy these constraints by allowing interactive,object-based intelligent communication between object data based on anunified presentation layer, an user definition and administration shelland an automated application/database definition generator interfacewhich accounts for seamless integration into the intelligent molecularobject technology.

[0072] They further remedy these constraints by allowing interactive,parallel, object-based intelligent communication in-between the dataitself to extract all relevant content in a fast, unique and automatedmanner, within complex network environments without the need ofupgrading or replacing current computer systems. The intelligentmolecular object pool technology provides seamless integration andreal-time answers to complex, multidimensional and interdependentqueries, but still maintains boundaries of data subsets to govern asecure, inter-data communicative global access. The intelligentmolecular object pool technology also provides a framework for scale-upand dynamically changing application needs in bioinformatics and thelife sciences.

[0073] Some of the major subsystems and procedures contributing to thisoperation and the advantages that follow there from are now described ingreater detail.

[0074] I. Software Architecture for an Information Technology PlatformUsing Intelligent Molecular Objects

[0075] The software architecture for an information technology platformusing Intelligent Molecular Object (IMO™) software and processing methodaddresses all steps of data processing from data acquisition throughdiverse sources and instrumentation to final output of diverse dataanalysis results.

[0076] In the first step, this technology uses engine components tostandardize and/or normalize data from diverse sources to make thoseotherwise different data comparable. The engines provide a means toaccurately compare, thus allowing one to test for identity, increase ordecrease in values or functional relevancy and the like. In particular,algorithms for tracking and normalization of object data (ObjectNormalization Engine, ONE) or image data (Global Image Normalization,GIN) are provided. These algorithms allow one to extract variable andnon-variable regions within a set of data and generate a global standardto which all data can be referred. By applying these algorithms,adjustments to all necessary parameters in a multidimensional data setcan be made automatically and simultaneously. Within the describedarchitecture, these algorithms can be applied in external modules orplug-in-format for other applications as well as for access via intranetor Internet.

[0077] Next, the architecture uses uniquely defined data objects, the“Intelligent Molecular Object” (IMO) as its data records. Each theobject consists of sets of functional layers (property panes). Theseproperty panes are activated or disabled via a Property Pane Controller(PPC). Each object is represented by a Unique Identifiers (UID), whichgoverns object data security and access permissions via the ObjectAccess Manager (OAM), and additional layers which define origin of theobject within the network (Object Root Router, ORR) and route contentand results interactively (Interactive Content Router, ICR) across thenetwork in a standardized fashion. A Status Management Component (SMC)monitors data integrity, command history and GLP/GMP-compliance via atable-based Object State Engine (OSE). The object state engine providescontrol for any object activity in real-time, logs activity records,provides GLP/GMP compliant experiment state assignment, state managementfor object data on the network, information request ranking andvectorized, direct addressing of data subsets (Vector Subsets, VSS) tominimize network traffic. This processing engine also handles externalquery submission and result synchronization for inter-object queries.All these processes allow the object to communicate intelligently viaVSS, and keep track of their interactions. Using Meta-data Indices(MDX), workspace-oriented VSS and Object Pane Descriptors (OPD) accountsfor quick and direct communication with diversified applications anddatabases via an Object Query Interface (OQI). An integrated ApplicationTranslator Link (ATL) communicating via the OAM allows for applicationintegration. Additionally, functionality is provided for DirectInformation Interchange (DII) between objects, graphical preview of theobject data (Object Graph Preview, OGP) and raw data matrix structuredescription (Raw Data Matrix, RDM; Matrix Structure Definition, MSD).

[0078] Next, the architecture provides an applications framework withinthe IMO technology, the Intelligent Object Handler (IOH), describingsets of user interactions and object environment definition protocols.This IOH is comprised in general of a set of processing engines andaccess interface protocols. These protocols provide methods andfunctions for preparation and presentation of data objects (IMOApplication Framework, IMO-A) for interaction within heterogeneousenvironments. A Unified Presentation Layer (UPL) within the IOH providesa web-enabled Graphical User Interface (GUI) to integrate components ormodules from diverse applications, laboratory systems environments, andto act as handler for IMO data (IMO Handler, IMO-H). Additionalcomponents include a User Definition Administration Shell (UDA), aMaster Query Component (MQC) and an interface to automate the query ofapplication and database requirements via an Application DefinitionGenerator (ADG). The creation and initiation of new IMO data is providedvia an integrated IMO Generator (IMO-G). A Direct Instrument Acquisition& Control Interface (DIAC) and a component for Automated ApplicationAssembly (AAA,) provide integration of real-time data acquisition andanalysis. Data Type Translators (DTT) are provided to integrateautomated transformation from heterogeneous data sources into IMO datain real-time. Automated normalization of data by calibration withstandardized empirical criteria within the workspace IMO StandardizationTechnique (IMO-S) is managed through integrated meta-data tags andpointers. Several access interfaces are also integrated at the IOHlevel. Next, an Object Translation Engine (OTE) is integrated, whichgoverns interactions (such as transformation, integration andinformation access) between IMO data and other diverse data environmentsto enable real-time communication. Such processes automaticallydetermine other data structures, look up functional information of thedata, create descriptors which correspond to object property panes anddetermine application type and access to IMO's in real-time. All theengines and interfaces establish the connection to the legacy world andprovide bi-directional, multidimensional, secure access to applications(Application Translation Interface, ATI), for queries via OQI, forresult generation (Result Generation Interface, RGI) and forsynchronization with offline legacy systems (Legacy SynchronizationInterface, LSI). Additionally, learning engines such as a KnowledgeExtraction Engine (KEE) or Distributed Learning Engine (DLE) and thelike can be implemented within the IOH.

[0079] Next, the architecture provides processes, which govern a globalvirtual data pool, the Intelligent Object Pool (IOP). The processescontain definitions for subsets, called Intra-Pools (iPools) regulatedby boundary protocols, which define integrity and persistence of IMOrelationships. IOP components comprise iPool boundary interfaces, iPoolmeta-data query and content access interfaces and iPool content orderingdefinitions and protocols. iPool boundary interfaces include the iPoolSecurity Authentication (iPSA) component, which provides securityauthentication; the iPool Integrity Assessment (iPIA) and ObjectIntegrity Assessment (OIA) components, which provide data integrity andpersistence; and the iPool Availability Monitoring (iPAM) and iPoolExchange Protocols (iPEP) components, which define and controlavailability and exchange at the IMO level. IPool Meta-data querydefinition interfaces are provided by Object-to-Object Query Meta-data(OQM), Real-Time Meta-data Link (RML), iPool Meta-data Index (iMDX), andiPool-to-iPool Query (PPQ) components. These processes apply interactivepresorting and exclusion algorithms, provide object clustering, objectresult clustering and object-to-object interaction rules, and enablerapid, relevant data access via real-time meta-data queries orderedwithin the iPool on the IMO level. iPool content access and orderingdefinitions and protocols include an Aggregate Meta-data Index (aMDX),Aggregate Real-time Significance Generator (aRSG) which integrate resultmerging algorithms and real-time answer generation. These iPool contentaccess protocols and order definitions allow for object-to-analysistools interactions, real-time result aggregation and real-time exclusionof irrelevant object data layers. Additional components include an IMOZoomer (IMO-Z), which defines the proximity of individual IMO datawithin the IOP and enables multidimensional IMO data viewing andfunctional ranking.

[0080] Through the functionality detailed above, the IOP provides anengine for global result aggregation (Result Aggregation Engine, RAE)and instant answer output across diversified data subsets and aninterface to assess integrity of iPools within the virtual, global datapool.

[0081] Engines, interfaces and components comprising methods, functions,and definitions are provided, to define and describe a unique,data-enabling software architecture (IMO IT Platform). These engines,interfaces and components implement an information technology platformwhich utilizes Intelligent Molecular Object (IMO™) data and consists ofa common framework comprising always-on as well as event-drivenprocessing engines, access interfaces, plug-in modules and othercomponents.

[0082] The IMO IT Platform architecture defined and described belowaddresses all steps of data processing from data acquisition throughdiverse sources and instrumentation to final output of diverse dataanalysis results reports.

[0083] The IMO IT Platform utilizes uniquely defined data objects,“Intelligent Molecular Object” data objects as its data records. EachIMO consists of sets of functional layers (property panes), describingcontent and providing certain functionalities to the object. Theseproperty panes are dynamically activated or disabled via a Property PaneController (PPC), function of which is to allow or block access based onuser privileges, data pool definitions and the like.

[0084] Each IMO is represented by an Unique Identifier (UID) containedwithin the identity pane, so it can be addressed and identified on anynetwork directly via its ID. The identity pane also governs object datasecurity and access permissions via the Object Access Manager (OAM), anintegrated part of the PPC to initiate object communication. Next, eachIMO contains a layer, which contains information defining the origin ofthe object within the network (Object Root Router, ORR) and its owner.Next, each IMO contains a layer, which routes content and resultsinteractively (Interactive Content Router, ICR) across the network usingstandardized protocols.

[0085] Next, a Status Management Component (SMC) monitors data integrityand command history in GLP/GMP-compliance via a table-based Object StateEngine (OSE). The Object State Engine consists of processes whichcontrol any object activity in real-time, log activity records, provideGLP/GMP compliant experiment state assignment and state management forobject data on stateless networks. In addition, the Object State Enginehandles information request ranking and vectorized, direct addressing ofdata subsets (Vector Subsets, VSS) to minimize network traffic. Thisprocessing engine also handles external query submission and resultsynchronization for inter-object queries by providing routing, propertypane access clearance and direct, workspace-oriented VSS addressing. Allthese processes allow the object to communicate intelligently via VSS,and keep track of their interactions.

[0086] Next, the IMO includes Meta-data Indices (MDX) layer for rapidaccess, and Object Pane Descriptors (OPD) which allow for quick anddirect communication with diversified applications and databases via anObject Query Interface (OQI), which allows for object-level directInformation Interchange (DII) between objects.

[0087] An integrated Application Translator Link (ATL), communicatingvia the OAM and ICR, accounts for integration of external applicationsand/or remote application status inquiries. Next, functionality isprovided for graphical preview of the object data (Object Graph Preview,OGP) and raw data matrix structure description (Raw Data Matrix, RDM;Matrix Structure Definition, MSD).

[0088] The architecture defines an applications framework within the IMOtechnology, the Intelligent Object Handler (IOH), which provides sets ofuser interactions and object environment definition protocols for theIMO data. This IOH is comprised in general of a set of processingengines and access interfaces. A Unified Presentation Layer (UPL) withinthe IOH provides a web-enabled Graphical User Interface (GUI), whichintegrates data, components and/or analytical and processing modulesfrom diverse applications and laboratory systems environments. Ingeneral, these protocols provide for preparation and presentation ofdata objects for interaction within heterogeneous environments (IMOApplication Framework, IMO-A).

[0089] To ensure automated, real-time normalization of data using one orseveral calibrations with empirical criteria within the workspace, theIMO Standardization Technique (IMO-S) is provided, which activatesengine components for standardization and normalization throughutilization of integrated meta-data tags and VSS pointers. These enginecomponents are defined by the following methods and functions, whichstandardize and/or normalize data from diverse sources to make thoseotherwise different data comparable. The engines provide a means toaccurately compare, thus allowing to test for identity, increase ordecrease in values or functional relevancy and the like. The followingalgorithms for tracking, standardization and/or normalization of objectdata (Object Normalization Engine, ONE) or image data (Global ImageNormalization, GIN) are defined. These algorithms allow for theextraction of variable and non-variable regions within a set of data andgenerate a global standard to which all data can be referred.

[0090] In the case of ONE, which is described in but not restricted tothe following example in the field of Life Sciences, the data arecomprised of numeric matrices, text annotations, chemical structureinformation, chirality information, spectral information, sequenceinformation and the like.

[0091] In the case of GIN, described by but not limited to the followingexample in the field of Life Sciences, the data are informationcontained in fluorescent and/or otherwise visibly stained 1D or 2D gelelectrophoresis images, array images, microscopic images and the like,all of which may differ in image acquisition parameters, detectiontechnique, intensity, color, positional distortions of zones, bands,spot or other regular or irregular objects contained in the imageswhich, in consequence, relate to certain macromolecule properties, suchas size/molecular weight, isoelectric point, concentration, biologicalactivity and the like. By applying algorithms, which define a vectorsubset for workspace selection in a single or a set of images, onlythose, typically relatively small areas of the images are processedwhich are needed to achieve relevant comparison. Such, data transferbetween different objects and for temporary storage and processing vianormalization, is reduced to the subsets for speed and efficiency. Byreference to either a common, global standard or a dynamically obtained,averaged reference from all data included within the comparison query,adjustments to all necessary parameters in a multidimensional data setcan be made automatically and simultaneously in parallel. Since thoseprocesses apply only to temporarily extracted small data subsets,several different request on the same object may be processed at thesame time. Since in each case only vector subset are generated, no rawdata alteration occurs and GLP/GMP-compliant data integrity ismaintained. Within the described architecture, the algorithms can beapplied as processing engines, in external modules or in plug-in-formatsfor other applications as well as for remote access via intranet orInternet.

[0092] Engines, interfaces and components provided within the IOH toprovide an integrated analytical framework, including but not limited tothe following. A User Definition Administration Shell (UDA) interface isprovided, which creates, modifies and administers user profiles andprivileges and defines rules for users within individual subsets ofdata, called Intra-Pools (iPools), as well as group memberships andtopic-related access rights. A Master Query Component (MQC), isprovided, which creates complex, multidimensional queries, containingpre-defined, configurable subsets of forms commonly used, but notrestricted to, in diverse areas of Life Sciences. An ApplicationDefinition Generator (ADG) component is provided, which automates thequery of application and database requirements and is comprised withinrelated translation components to generate tables required forintegrated real-time property pane presentation at the data objectlevel. An IMO Generator (IMO-G) component is provided, which creates newIMO data from existing data resources, or from newly acquiredinstrumentation data. An IMO handler (IMO-H) component is provided,which initiates user commands and queries at the IMO level via the useof integrated meta-data tags and pointers. A Direct InstrumentAcquisition & Control Interface (DIAC) is provided, which enablesbi-directional real-time communication between the IOH, the IMO anddiverse instrumentation. An Automated Application Assembly (AAA)component is provided, which enables integration of real-time dataacquisition and analysis functionality through just-in-time (JIT) modulelinking. A Data Type Translation (DTT) component is provided, whichintegrates translation tables from the ADG from heterogeneous datasources into IMO data in real-time. The DTT are comprised of dynamicallygenerated sets of reference tables to provide rapid access through datastructure definitions.

[0093] Several engines and access interfaces integrated at the IOH levelare defined, which utilize the meta-data tags and pointers to passinformation between internal and external components. All the enginesand interfaces establish the connection to the legacy world. An ObjectTranslation Engine (OTE) is included, which governs interactions (suchas transformation, integration and information access) betweenintelligent object data and other diverse data environments to enablereal-time communication. Such processes automatically determine otherdata structures, look up functional information of the data, createdescriptors which correspond to object property panes and determineapplication type and access to IMO's in real-time. An ApplicationTranslation Interface, (ATI) is defined, which provides bi-directional,multidimensional, secure access to applications for queries via OQI. AResult Generation Interface (RGI) is defined, which provides validated,assembled, ranked and tabulated results to the RAE, enabling thegeneration of output reports across diversified data subsets. A LegacySynchronization Interface (LSI) is defined, which providessynchronization with offline legacy data. Additionally, learning enginessuch as a Knowledge Extraction Engine (KEE) or Distributed LearningEngine (DLE) and the like can be implemented within the IOH.

[0094] Next, the architecture provides the following interfaces,component processes and engines which enable and govern a global virtualdata pool comprised of IMO data, the Intelligent Object Pool (IOP). Thecomponent processes contain definitions for subsets, called Intra-Pools(iPools), regulated by boundary protocols, which define integrity andpersistence of IMO relationships. IOP components are defined, whichcomprise iPool boundary interfaces, iPool meta-data query and contentaccess interfaces and iPool content ordering definitions and protocols.

[0095] iPool boundary interfaces are defined, which include the iPoolSecurity Authentication (iPSA) component, which provides securityauthentication; the iPool Integrity Assessment (iPIA) and ObjectIntegrity Assessment (OIA) components, which provide data integrity andpersistence; and the iPool Availability Monitoring (iPAM) and iPoolExchange Protocols (iPEP) components, which define and controlavailability and exchange at the IMO level.

[0096] iPool Meta-data query definition interfaces are provided byObject-to-Object Query Meta-data (OQM), Real-Time Meta-data Link (RML),iPool Meta-data Index (iMDX), and iPool-to-iPool Query (PPQ) components.These processes apply interactive presorting and exclusion algorithms,provide object clustering, object result clustering and object-to-objectinteraction rules, and enable rapid, relevant data access via real-timemeta-data queries ordered within the iPool on the IMO level.

[0097] iPool content access and ordering definitions and protocols areprovided, which include an Aggregate Meta-data Index (aMDX), AggregateReal-time Significance Generator (aRSG) which integrate result mergingalgorithms and real-time answer generation. These iPool content accessprotocols and order definitions allow for object-to-analysis toolsinteractions, real-time result aggregation and real-time exclusion ofirrelevant object data layers. Additional components include an IMOZoomer (IMO-Z), which defines the proximity of individual IMO datawithin the IOP and enables multidimensional IMO data viewing andfunctional ranking.

[0098] It is evident from the above description, that this IMO ITarchitecture allows for decision empowering, real-time answers tocomplex, multidimensional, interdependent queries by providing theinfrastructure for a global, comprehensive analysis of otherwise notaccessible vast, inconsistent sets of data.

[0099] The following examples are offered by way of illustration and notby way of limitation.

[0100] In a typical life sciences example, a 2-dimensionalelectrophoretic protein separation is carried out and the silver-stainedseparation pattern is introduced in an imaging workstation to obtain ahigh resolution, high dynamic range image representation of the spotpattern (typically, about 2500-6000 individual protein spots/image).Each of those spots represents a single protein at a defined expressionstage in a specific cell environment, e.g. in this example, human livercells. These pattern reflect also genetic differentiations and/ormodifications, e.g. in case of human samples, the origin of the cell,gender, age, race, physical condition of the individual and the like.

[0101] It is obvious from the above, that such pattern represent ininherent multidimensional complexity, all of which even more expressedby laboratory-to-laboratory deviations in performing the analyticalprocedure, sometimes also on different types of instrumentation. Toanalyze such a pattern for, for instance the increase or decrease inconcentration based on a pathological disease condition or fordrug-induced changes on certain proteins in enzyme-, inmunologicalactivity and the like, non-patient specific data have to be separatedfrom those common in all pattern. A large series of such gels must beanalyzed, standardized and compared to achieve this goal.

[0102] In the example, the IMO platform technology will do thefollowing: A scientist on a laptop (1) in site A in the USA logs ontothe IMO platform; the UDA within the IOH verifies the login, sets userpermissions and encryption level, generates a session ID and starts asession for (1) in the IOH. Next, the scientist (1) uses the menu in theUPL to acquire instrument data, in this example gel image data. The DIACwithin the IOH communicates with the imaging workstation (2) to remotelystart image acquisition, the IMO-G creates a new data objects for thecurrently acquired image. This new IMO consists now of a UID pane, whichuniquely identifies the IMO via 10-character key across the network. TheUID pane also defines object type, contains information about the origin(ORR) on the network (on 1), the owner (creator) of the IMO, how content(the raw image data in this case) is routed (ICR) interactively on thenetwork (in this case, the raw image file at the imaging workstation (on2)), of an OSE pane, in which the first 2 entries are created via theSMC (an object creation record, and the current data state entry, “dataacquisition in progress”, an indexed multi-digit number from the GLP/GMPstate assessment table), a OPD pane describing which panes arefunctionally defined, a dynamically updated OGP (displaying aprogressive thumbnail view of the image in real-time as it is acquired)and a RDM pane consisting essentially only of file type description andpointers to the original image file, thus there is no data redundancyanywhere on the entire network. When image acquisition is complete, theSMC on the IMO adds another status entry “data acquisition completed” tothe IMO state history log and adds final data MSD's to the RDM pane.

[0103] Simultaneously, another scientist (3) in site 2 in Japan logsonto the IMO platform; the UDA within the IOH verifies the login, setsuser permissions and encryption level, generates a session ID and startsa session for (3) in the IOH. Next, the scientist (3) uses the menu inthe UPL to submit a global query about gel image data, in this case,describing a defined disease-related change in protein expression ofpeptides with an iso-electric points around 5.5 and a molecular sizeranging between 80 k DA-120 k DA in liver cells from white, human maleswith an age above 50. The MQC within the IOH analyzes the query byproviding the IMO-H with VSS for the appropriate workspace definitionswithin the 2D gel image data (based on the entered pI and sizeconstraints, only a small fraction of each images is relevant to thequery), which, in turn, gates the query to IMO's via OQI. Based on MDXlinks, the PPC will only inquire those iPools and IMO's with matchingOPD's. The OAM on each such IMO checks access privileges, triggers thePPC, sends update request to the OSE, extracts partial image informationfrom the original RDM for temporary storage to be processed via ONE andGIN for image workspace normalization and comparison. Standardizedcomparisons (in this case, the protein spot location in the individualIMO RDM subset, and its concentration, represented by its integrated,optical density calibrated intensity) within the VSS are reported backvia ICR in each IMO to the RGI at the IOH level, which creates rankedoutput. Similarly, MDX-based, the OTE at the IOH level performs datatranslation of workspace data from other databases using the ATI tointegrate those relevant data into the result-ranking. During this time,another scientist (4) in site B in the USA logs onto to the IMOplatform, and performs a similar, but not identical query. The DLEimmediately addresses the MQC to define a new VSS only within thealready addressed, active IMO's RDX's. The RAE at the IOP aggregates theIMO results, sorts them based on relevancy and similarity, reports tothe KEE and DLE for dynamic MDX update, and posts the final tabulatedanswer back to the IOH via RGI. Proximity of integrated data is relatedto the IMO-Z for graphical representation. The UPL now presents theaggregated, ranked answers to the query in several graphical andnumerical windows to the scientist (3), including the newly generatedimage from scientist (1). On a different location and network, at thesame time the local UPL in scientist's (4) computer displays theaggregated answer for his query. In the above example, for scientist (1)212 peptides and for scientist (4) 96 peptides were identified, whichdiffer in their expression level, amongst a set of >500000 relevant 2Dgel images with approx. 3000 individual spots each.

[0104] It is noted, that in a conventional database environment,processing of the query would require the analysis of the entire gelimages and their annotations, at the required resolution typically atfile sizes around 2-5 MB each, and the alignment (normalization) of theimage in its entity, thus, requiring enormous amounts of data to beprocessed. The IMO IT platform technology's dynamic workspacedefinitions via VSS reduces this so significantly, that alignment,matching and comparison are reduced to, in this example, about 40-60 kBdata each (or approximately, by 60-fold), allowing real-time resultaggregation.

[0105]FIG. 1 is a representation of an embodiment of the general IMO ITarchitecture, depicting relationships between framework, engines,interfaces and other components. The depiction below is a representationof the general IMO IT architecture, depicting relationships betweenframework, engines, interfaces and other components. The verticaldividers represent, from left to right, front-end processing, access toanalysis/applications, and back-end processing. All acronyms areexplained elsewhere in this description.

[0106]FIG. 2 is a representation of functional relationships betweeninstruments, applications and diverse databases within the IMOarchitecture. The depiction below is a representation of functionalrelationships between instruments, applications and diverse databaseswithin the IMO architecture. Within each session, after Login, allcommunication between IMO's, instruments, applications and back-enddatabases and to the IOP is enabled at the IOH level. Real-time andbatch data acquisition from instrumentation, real-time and batchanalysis via external applications, and queries to the IOP (consistingof iPool subsets, diverse databases, and the like) is performed throughthe IOH engines and interfaces for both, local and remote access. Inaddition, the answer-generating processes are also interfacing with theIOH communication handling.

[0107]FIG. 3 is a representation of a multi-user network collaborativeresearch as described herein. The depiction below is a representation ofa multi-user network collaborative research as described under“Experimental”. Three geographical locations are in real-timeinteraction through a unified presentation GUI displayed locally,connected globally. Data acquisition, query and aggregated results(“answer”) are presented within the main UPL window of the IOH.

[0108]FIG. 4 is a representation of a flow chart of typical dataprocessing within the IMO IT architecture. The depiction below is arepresentation of flow chart of typical data processing within the IMOIT architecture.

[0109] In light of the description provided here and in the followingmore detailed description as well as the appurtenant figures, it will beappreciated that the invention provides an architecture, business modeland method of doing business related to searching for and analyzing datagenerally and in particular relative to biological, chemical, and lifesciences type information. Several exemplary embodiments are nowdescribed by way of example, but not limitation.

[0110] In one aspect, the invention provides a software architecture foran information technology platform, comprising of always-on andevent-driven, engines, interfaces and processes and using intelligentmolecular software data objects for interactive data records.

[0111] In another embodiment, this architecture is further defined suchthat the architecture further comprises one or more of: a. anIntelligent Molecular Object (IMO), a versatile, data-enabling softwareobject, which provides for real-time translation, integration, andobject-to-object/object-to-analysis tools communication at the objectdata level, to allow multidimensional, platform-independent complexqueries in real-time; b. an Intelligent Object Handler (IOH), whichprovides the application framework and user interface for IMO data, toallow for seamless integration of their benefits into legacy systems;and c. an Intelligent Object Pool (IOP), comprising one global virtualdata pool comprised of IMO data, which integrates diverse data resourceson any system or network to provide result aggregation and instantanswers across diversified data subsets.

[0112] In another aspect, the IMP of the architectural method andplatform is further defined to include one or more of: a. a uniqueidentifier (UID), comprising a property pane layer created at IMOgeneration, which provides typically a 10 byte, alphanumeric uniqueidentification on any system or network; b. an object access manager(OAM), a property pane layer which governs data security and accessaccording to UID permissions; c. an object root router (ORR), a propertypane layer which contains information to define the origin of the objectwithin the system or network; d. an interactive content router (ICR), aproperty pane layer which routes content and results interactivelyacross the system or network; e. a status management component (SMC),comprised of an object state engine and certain interfaces, whichmonitors data integrity and command history in GLP/GMP-compliance viastate history and governs table lookup actions via the ICR; f. aproperty pane controller (PPC), which controls the initiation of IMOcommunication according to activation by 3 a through 3 d, above; g.vector subsets (VSS) for automatic, dynamic, or user-defined workspacedefinitions, which provide vectorized, direct addressing of data subsetsfor the ICR to minimize network traffic; h. meta-data indices (MDX), toprovide efficient access via dynamically updated meta-data descriptionrelevant to extant data queries and definitions; i. object panedescriptors (OPD), which provide information about each object propertypane and their function as required for direct communication withdiversified applications and databases; j. an interface for directinformation interchange (DII), which provides the interface tocommunication at the object level; k. an application translator link(ATL), which activates the OAM and ICR to determine the property panesfor functional presentation and access within a given application ordatabase environment; 1. an object graph preview (OGP) pane, comprisinga limited resolution image and graphics viewer for quick graphical datareview, particularly of image data and spectral datasets; m. a raw datamatrix (RDM), comprising a property pane which provides the fullinformation subset for any data format or structure; and, n. matrixstructure definitions (MSD), which allows for data field mapping andenables vector access to specific data fields.

[0113] In another aspect, the architecture is further defined such thatthe architecture and accompanying process and method include the IOHwhere the IOH further includes: a. a unified presentation layer (UPL),which provides a web-enabled graphical user interface (GUI) to integratecomponents and/or modules from diverse applications, laboratory systemsenvironments and to act as handler for IMO data; b. a user definitionadministration shell (UDA), which sets ups and governs access privilegesto individual IMO data at the user-defined level and is accessiblewithin heterogeneous network environments; c. at least one engine fordata object normalization and standardization, image normalization andstandardization, IMO data translation, distributed learning, andknowledge extraction; d. at least one access interface to and in-betweeninstruments, data and applications, comprising interfaces which include,but are not limited to, direct instrument acquisition and control,application translation, direct object query, result generation, andlegacy synchronization; e. a master query component (MQC), createcomplex, multidimensional queries, containing pre-defined, configurablesubsets of forms commonly used, but not restricted to, in diverse areasof Life Sciences; f. an IMO generator (IMO)-G), an event-drivencomponent to acquire data from heterogeneous data resources, includingfrom ongoing data acquisition, in real-time and transforms deviceoutputs and heterogeneous data types to IMO data; g. an IMO handler(IMO-H), which enables user management of IMO data utilizing integratedmeta-data tags and pointers; h. an IMO application framework (IMO-A),which provides integration and access protocols to heterogeneousapplications and databases on the object level; i. an applicationdefinition generator (ADG), which automates the query and generation ofapplication and defines computing environments for the IMO datatranslation; j. at least one data type translator (DTT), which definethe data type dependencies for the IMO-G according to the applicationsand database environments defined by the ADG; and k. an automatedapplication assembly component (AAA), which provides for just-in-time(JIT) module linking.

[0114] In yet another embodiment or aspect, the architecture is furtherdefined such that the IOP includes one or more of: a. sets ofIntra-Pools (iPools), regulated by boundary protocols, which providedata subset management and the define integrity and persistence of IMOrelationships; b. iPool security authentication protocols (iPSA), whichauthenticates iPool data requests according to user login and objectdata identification; c. iPool availability monitoring protocols (iPAM),which define the iPool availability and access requirements of diversedata subsets; d. iPool exchange protocols (iPEP), which determine andgovern iPool data exchange protocols according to user-defined criteria;e. an object integrity-assessment component (OIA), which assess objectintegrity for security and QA/QC; f. sets of engines and interfaces toaccess and generate ranked results within the IOP, including but notlimited to an integrity assessment interface, a real-time meta-datalinking interface and an iPool-to-iPool query interface; g. an iPoolmeta-data index (iMDX), which provides dynamic, automated, anduser-defined meta-data indices at the iPool level; h. an aggregatemeta-data index (aMDX), which provides dynamic, automated, anduser-defined meta-data indices at the aggregate IMO level, inclusive ofall relevant data resources; i. an object-to-object query meta-datasorter (OQM), to generate temporary tables based on dynamic, automated,and user-defined meta-data indices; and j. an aggregate real-timesignificance generator (aRSG), which provides for significance detectionof values based on query parameters, meta-data indices when relevant,and IMO data ranking.

[0115] In one additional particular embodiment, the engines within thearchitectural platform and method are further defined to include: a. anobject state engine (OSE), which provides a continuously-running (alwayson) set of processes, which monitor and govern activities of IMO data,performing real-time recording, updating and logging functions inGLP/GMP-compliant format.

[0116] In another alternative embodiment, one or more engines within thearchitecture are further defined to include one or more of: a. a set ofIMO standardization techniques (IMO-S), comprising engines which providealgorithms for tracking, standardization and/or normalization of objectdata; b. an generic object normalization engine (ONE), which extractsvariable and non-variable regions within any set of object data andgenerates a global standard to which all data can be referred; c. anengine for global image normalization (GIN), which extracts variable andnon-variable regions within any set of image data and generates a globalstandard to which all data can be referred; d. an object translationengine (OTE), which is comprised of methods and functions for real-timemeta-data extraction and table generation of raw data matrix, dataobject, data field, data structure, data functional information, datatype, database type, and application type definitions for the OPD; e. adistributed learning engine (DLE), which provides algorithms fordynamic, automated, and user-defined hypothesis generation utilizingglobal data resources; and, f. a knowledge extraction engine (KEE),which provides algorithms for dynamic, automated, and user-definedsignificance discovery and report generation.

[0117] In a further embodiment of the architecture, the engines mayinclude: a. a result aggregation engine (RAE), to validate, assemble,rank and tabulate results passed from the IOH and to generate outputreports across diversified data subsets.

[0118] In yet a further embodiment of the architecture, the interfacesmay include: a. a direct information interchange interface (DII), whichallows for rapid analysis and results aggregation by providing theinterface for object-to-object and object-to-analysis tools via suchrelated interfaces and engines including, but not limited to the OQI,OTE, and the DLE.

[0119] In yet a further embodiment of the architecture, the interfacesmay include one or more of: a. a graphical user interface (GUI),utilizing web-enabling standards including but not limited to Java andXML; b. a direct instrument acquisition and control interface (DIAC),which provides bi-directional real-time communication between the IOH,the IMO and diverse instrumentation; c. an application translationinterface (ATI), to provide automated real-time detection of diversedata and applications and gate bi-directional access to the OTE, thusenabling functional, standardized integration of IMO data withinheterogeneous data and applications environments; d. an object queryinterface (OQI), comprising an interface for direct informationinterchange (DII) with IMO data, which initiates query analysis andresults aggregation; e. a result generation interface (RGI) to providevalidated, assembled, ranked and tabulated results to the RAE, thusenabling the generation of output reports across diversified datasubsets; and f. a legacy synchronization interface (LSI), to providepersistence and synchronization of offline legacy data.

[0120] In still another embodiment of the architecture, the interfacesare further defined to include one or more of: a. an iPool integrityassessment interface (iPIA), to asses data integrity within a definediPool for security and QA/QC; b. a real-time meta-data link interface(RML), which provides for rapid relevant data access based on queryparameters and MDX information; c. a pool-to-pool query interface (PPQ),which provides for query optimization based on query parameters andrelevant iPool data and meta-data intercommunication; and, d. an IMOZoomer (IMO-Z), which defines proximity and functional ranking ofindividual IMO data within the IOP and enables multidimensional IMO dataviewing to represent object relationships within the pool and inrelationship to other iPools.

[0121] In another embodiment, the invention provides a software orcombination software and hardware architectural platform that usesobjects for real-time, efficient, multidimensional, interdependentintelligent queries.

[0122] In yet another embodiment, this software architectural platformand the associated methods and procedures are implemented on generalpurpose computers, information appliances, and the like informationand/or computation devices, at least some of which are coupled tosimilar devices and servers on an interconnected network, such as theInternet.

[0123] When implemented as software, the software may be resident withina memory of the computer or information device and execute within aprocessor, microprocessor, or CPU of such device. Any conventionalcomputer or information appliance having suitable memory, processor, andinterface capabilities may be used, many of which types are known in theart.

[0124] An alphabetic list of IMO Information Technology Platformacronyms as used in this description is listed below: AAA AutomatedApplication Assembly ADG Application Definition Generator aMDX AggregateMeta-data Index aRSG Aggregate Real-time Significance Generator ATIApplication Translation Interface ATL Application Translator Link DIACDirect Instrument Acquisition & Control Interface DII Direct InformationInterchange DLE Distributed Learning Engine DTT Data Type TranslatorsGIN Global Image Normalization GUI Graphical User Interface ICRInteractive Content Router iMDX iPool Metadata Index IMO IntelligentMolecular Object IMO-A IMO Application Framework IMO-G IMO GeneratorIMO-H IMO Handler IMO-S IMO Standardization Technique IMO-Z IMO ZoomerIOH Intelligent Object Handler IOP Intelligent Object Pool iPAM iPoolAvailability Monitoring iPEP iPool Exchange Protocols iPIA iPoolIntegrity Assessment iPool Intra-Pool (data subsets) iPSA iPool SecurityAuthentication KEE Knowledge Extraction Engine LSI LegacySynchronization Interface MDX Meta-data Indices MQC Master QueryComponent MSD Matrix Structure Definition OAM Object Access Manager OGPObject Graph Preview OIA Object Integrity Assessment ONE ObjectNormalization Engine OPD Object Pane Descriptors OQI Object QueryInterface OQM Object-to-Object Query Meta-data ORR Object Root RouterOSE Object State Engine OTE Object Translation Engine PPC Property PaneController PPQ Pool-to-Pool Query RAE Result Aggregation Engine RDM RawData Matrix RGI Result Generation Interface RML Real-Time Metadata LinkSMC Status Management Component UDA User Definition and AdministrationShell UID Unique Identifier UPL Unified Presentation Layer VSS VectorSubsets

[0125] II. Intelligent Molecular Object Data for Hetrogeneous DataEnvironments with High Data Density and Dynamic Applications Needs

[0126] In intelligent molecular object (IMO) data for heterogeneous dataenvironments aspect, structure and method are provided for object datacreation and identification, root data and meta-data content routing,data status management, meta-data indexing, and object query andresponse management for diversified data in networked Life Sciencesapplications environments.

[0127] In the data creation and identification method, the user query,command, or data acquisition action invokes the unique object identifier(UID) pane, which identifies each data object and implements uniqueidentity, security and access definitions. The object root router (ORR)defines the origin of the object within the network and directs storageof the object within the database. In the meta-data content routingmethods, the user query, command, or data acquisition action invokes theinteractive content router (ICR) pane, which defines wherequery-relevant content and/or results will be directed within thenetwork for analysis or presentation. In the data status managementmethod, the status management component (SMC) monitors data integrityand records the command history according to GxP-compliant LIMSrequirements. Simultaneously in the meta-data indexing method, themeta-data index (MDX) pane creates an index of data information andmakes the meta-data available to the object pane descriptor (OPD). Inthe object query and response method, the object pane descriptor (OPD)determines the relevant panes for access and presentation.Simultaneously, the application/database definition router (ADDR)determines and relays the application/database requirements to theapplication translator link (ATL). The application translator link (ATL)activates the object access manager (OAM), which determines themeta-data panes for functional presentation and access within a givenapplication or database environment. Simultaneously, the object queryinterface (OQI) initiates object meta-data analysis and query resultsaggregation via the object-to-object direct information interchange(DII) and relays significant query outcomes to the object panedescriptor (OPD) for presentation to the user. An object graph preview(OGP) pane option is included within the object including a limitedresolution image/graphics viewer for quick graphical data review of dataobjects containing graphical information. Other extensible optionsinclude ownership management; use tracking; selective access; objecthandling and storage technology.

[0128] Methods are provided to define and describe the architecture forinteractive, intelligent molecular object (IMO) data structures.

[0129] Objects are defined in a hierarchical, multi-layered(“pane”)-style, which accounts for secure, property-driven functionalbi-directional access to the data contained in these panes. Each objectis defined by a minimal set of panes as described in detail below, butmay or may not have additional panes attached with unique,functionality-driven properties. The minimal set of panes contains thefollowing elements:

[0130] an unique identifier (UID) pane, which allows for secureidentification of the IMO on the network; it consists of severalelements which allow for routing to its origin (object root router, ORR)and distributed routing of its content or selected, object-specificquery-driven results (intelligent content router, ICR) within definedobject-to-object communication parameters. The UID pane also containsobject creator information, access privilege information and commonsecurity elements to protect the IMO from unauthorized access. Inaddition, the current user information and its relationship to theobject reside temporarily in this pane and are updated dynamically;

[0131] a status management component (SMC) pane, which monitors dataintegrity and command history in G*P-compliant LIMS-style. This objectstate engine (OSE) contains coded data access information such as dataacquisition completed, calibration information, applied datatransformation or analysis processes, validation management and thelike. Information contained herein is used for data integrityprotection, rollback and process history;

[0132] a metadata index (MDX), which allows for fast access to the IMObased on object functionality and description (an indexed and ranked“data-about-data” dictionary for type and topic predefined searching ofquery-relevant intelligent molecular objects (IMO's));

[0133] an object pane descriptor (OPD), which allows for explicitdefinition of pane structure, order and function. This pane alsoincludes an application/database definition router (ADDR) to call properanalysis tools based on the object panes available;

[0134] an application translator link (ATL) pane which providesalgorithm to allow for inter-application communication and contains anobject access manager (OAM) for application integration. This paneallows for quick and seamless application integration and provides thefunctionality for rapid and dynamic development of new applications;

[0135] an object query interface (OQI) for object-to-object directinformation interchange (DII), which processes the query internallywithin the IMO; and;

[0136] a raw data matrix (RDM) pane containing the full informationsubset in any data format or structure; and; a matrix structuredescriptor (MSD) which allows for data field mapping and vector accessto individual data fields.

[0137] Optional panes may include an object graph preview (OGP) panecomprising of a limited resolution image/graphics viewer for quickgraphical data review, particularly of image data or spectral datasetsand the like.

[0138] It is evident from the above description, that this objectarchitecture allows for real-time answers to complex, multidimensional,interdependent queries by providing the infrastructure for a global,comprehensive analysis of otherwise not accessible vast, inconsistentdata sets.

[0139] The following examples are offered by way of illustration and notby way of limitation. Data from 2Dimensional Gel Electrophoresis (2DE)typically exhibit an intrinsic complexity due to the reproducibilitychallenges inherent in this multi-step experimental technique. Each ofsuch gel comprises over 5000 individual peptide spots that relate in itsentity to a defined stage in the cell metabolism. Such image data wereused in a global query to obtain characteristics of significant proteinexpression in human liver cells at different disease states. Only largerpeptides with isoelectric points (pI's) between 5.0-7.0 and within asize range of greater than 96000 Dalton (DA) were of therapeuticinterest and only validated experiments were included.

[0140]FIG. 5 is a representation of the user interface of an intelligentmolecular object (IMO) showing its unique identifier pane (UID). Thedepiction is a representation of the user interface of an intelligentmolecular object (IMO) showing its unique identifier pane (UID). Itcontains object creation data; the location of the object on thenetwork; information routing information; user data, session andconnection verification and security settings such as encryption levelor password protected access.

[0141]FIG. 6 is a representation of the user interface of an intelligentmolecular object (IMO) showing its status management component (objectstate engine, OSE). The depiction is a representation of the userinterface of an intelligent molecular object (IMO) showing its statusmanagement component (object state engine, OSE). In the displayedexample of 2DE data, the experimental state is validated. Means for aquick review of the object history are provided including significantevents since its creation such as calibration, analysis and annotation.

[0142]FIG. 7 is a representation of the user interface of an intelligentmolecular object (IMO) showing the optional object graph preview (OGP)pane comprising a limited resolution image/graphics viewer. Object graphpreview (OGP) pane example on 2Dimensional Gel Electrophoresis proteinexpression data. The low-resolution image viewer depicts an overview ofthe entire gel in a large-style thumbnail view with an inset of theimmediate workspace area used in the query.

[0143] In light of the description provided relative to the overallarchitectural platform and the following more detailed description andfigures, several exemplary embodiments are now described for this aspectof the invention by way of example, but not limitation.

[0144] In one aspect, the invention provides an architectural platformand framework as well as method for using interactive Objects forreal-time, efficient, multidimensional, interdependent intelligentqueries.

[0145] In another aspect, it provides an Intelligent Object consistingof a set of functional layers also referred to for convenience as“Panes”. It further provides methods and procedures for creating theIntelligent Objects as well as the structures for intelligent objects,whether molecular or other object types dealing with different datatypes or subject matter. The invention also provides a Unique ObjectIdentifier (UID) Pane within the object, which identifies each objectand contains rules for object data security and access permissions. Inanother aspect, it provides an Object Root Router (ORR) Pane within theobject, which defines the origin of the object within the network. Inanother aspect, it provides an Interactive Content Router (ICR) Panewithin the object, which defines where content and/or results will bedirected within the network.

[0146] In another aspect or embodiment, the invention provides a StatusManagement Component (SMC) Pane within the object, which monitors dataintegrity and command history in G*P-compliant LIMS-style. In yetanother embodiment, the invention provides a Meta-Data Index (MDX) Panewithin the object. In yet another embodiment, it provides an Object PaneDescriptor (OPD) within the object, which includes anApplication/Database Definition Router (ADDR).

[0147] In even another embodiment, the invention provides an ApplicationTranslator Link (ATL) Pane within the object, which includes an ObjectAccess Manager (OAM) for application integration. It may further providean Object Query Interface (OQI) for Object-to-Object Direct InformationInterchange (DII), as well as an Object Graph Preview (OGP) Pane withinthe object including a limited resolution image/graphics viewer forquick graphical data review, and/or a Raw Data Matrix (RDM) Pane withinthe object including a Matrix Structure Descriptor (MSD).

[0148] These aspects and embodiments are merely exemplary and thestructures, methods, procedures and elements may be combined in numerousadditional ways to provide further and different embodiments.

[0149] III. Object State Engine for Intelligent Molecular Object DataTechnology

[0150] With respect to the Object State Engine (OSE) aspect, structure,methods and functions comprising a set of processes are provided for:request for creation of intelligent molecular objects; assignation ofunique object identification; object activity monitoring and historyrecordation; GLP/GMP compliance state table lookup and state validationassignment; security and privilege access management; status memory andback-end interaction for stateless networks; validation status ranking;vector subset definition for dynamic information exchange;object-to-object and external query processing.

[0151] In the object creation and unique identification assignmentprocesses, first a flag is set, that the object does not exist. Then,this flag triggers an object creation module to generate an intelligentmolecular object (IMO), comprising of a set of interactive data objectproperty panes. An object root router (ORR) pane is assigned whichdefines the origin of the object within the network. Simultaneously, aunique object identifier (UID) pane is assigned, which identifies eachdata object and implements identity, security and access definitions.Next, the core processing and timing functionality for activitylistening mode (ALM) is generated, and the initial object state historyis created. This module reports its completion state back to the stateengine.

[0152] In the object activity, history and validation processes, the ALMprovides continuous object activity monitoring and state historyrecordation, which provides an activity record comprising of action(utilizing a table), user information and time/date stamp(“what/who/when”) information. Any such entry is called object activityrecord (OAR), which, in sequential order, comprise the object statehistory. Next, all actions are validated by the assignment of a codedstate according to an ISO 9000/ANSI-compliant table for Good LaboratoryPractices/Good Manufacturing Practices (GLP/GMP) regulatory compliance.

[0153] In the access management, status memory and back-end processes,access to object property panes is granted to all object- andobject-to-object activities based on security protocols and privilegedefinitions. Upon any access request, a status flag is set at the coreof the object state engine, which triggers data security processing onthe individual object level. Simultaneously, a status definition bufferis maintained for state-less networks and action consequences aretransmitted to back-end systems upon completion of state updates.

[0154] In the validation status ranking, objects and/or objectproperties are ranked based on validation state information. This rankis used to provide validity and query-relevance for fast informationinterchange.

[0155] In the vector subset definition for dynamic informationinterchange processes, a state-related event-driven process componentdefines vectors to point to limited workspace subsets of object datawithin the data matrix, which enables real-time, dynamic andstandardized direct information interchange.

[0156] In the query state processing, an event-driven process componenthandles external query submissions to the object. Queries, commands anddata acquisition actions invoke an interactive content router (ICR) panewithin the object, which defines where query-relevant content and/orresults will be directed within the network for analysis orpresentation. Simultaneously, a process component sets the timing forobject-to-object query result synchronization and initiates resultaggregation by triggering an output request to the unified presentationinterface via ICR.

[0157] The described object state engine defines order and timing forprocessing of, and interaction with, object activities, therebyretaining object integrity and dynamic state monitoring in data exchangeover otherwise stateless global networks.

[0158] Methods and functions are provided for a set of processes, whichcomprise an intelligent object state engine. Purpose of the engine is tomonitor and govern activities of intelligent molecular objects andin-between such objects in real-time.

[0159] The first component comprised in the state engine processes arequest to create an object and assign a unique identifier to it.Additionally, this process generates its first object state historyrecord and activates state monitoring (“activity listen mode”, ALM).This component provides the core processing and timing functionality forthe state engine.

[0160] Next, there is a process component of the object state engine,which monitors any object activities or transactions with the object andadds an activity record to the object state history, consisting of“what/who/when?”-information. This component also may transmit securityalerts back to the network and/or update transaction logs.

[0161] Further, the state engine contains a process component, whichrelates all activities to Good Laboratory Practices/Good ManufacturingPractices (GLP/GMP)-compliant, laboratory information management system(LIMS)-style experiment data states. This process also validates thecurrent action by assigning a defined state to the object, utilizing alookup table.

[0162] Next, the state engine contains a process component, which allowsor denies access to the object and permits object-to-object activitiesbased on security protocols and privilege definitions. This process setsa status flag and reports directly to the core of the state engine,which monitors activity, thus governing data security on the individualobject level.

[0163] Also contained in the state engine is a process, which utilizes asmall buffer as status memory for state-less networks, which allows totransmits action consequences back to the backend system upon stateupdate completion.

[0164] Next, the state engine contains an event-driven processcomponent, which uses a validation state based information exchange torank objects or object properties for relevancy and faster access.

[0165] Next, the state engine contains a state-related vector definitionof object data subsets for dynamic information interchange to define alimited workspace area within each data set for direct, real timeaccess.

[0166] Lastly, the state engine contains a query processing component,which handles external query submissions to the object. This componentalso times object-to-object query result synchronization and initiatesresult aggregation by triggering an output request to the unifiedpresentation interface.

[0167] It is evident from the above description, that this object stateengine allows to track object states in real-time in otherwisestate-less network environments by providing the infrastructure for aglobal, comprehensive and secure monitoring and updating.

[0168] In light of the description provided relative to the overallarchitectural platform and this additional detailed description, severalexemplary embodiments are now described for this aspect of the inventionby way of example, but not limitation.

[0169] In one aspect, the invention provides a continuously-running setof processes, comprising an object state engine monitoring and governingany activities of intelligent molecular objects in real-time. It alsoprovides a process component of the object state engine to trigger amodule for creating an object if such object does not exist, andassigning a unique identifier to it; as well as a set of processcomponents within the object state engine, which monitor objectactivities or transactions with the object and record its activityhistory. Aspects and embodiments of the invention further provide aprocess component of the object state engine, which relates activitiesto Good Laboratory Practices/Good Manufacturing Practices(GLP/GMP)-compliant, laboratory information management system(LIMS)-style experiment data states and validates the current action byassigning a defined state to the object; a process component of theobject state engine, which governs access to the object andobject-to-object activities based on security protocols and privilegedefinitions; a process component of the object state engine, whichmaintains status remembering in state-less networks and transmits actionconsequences back to the backend system; and a process component of theobject state engine, which ranks requests for information exchange basedon annotation or validation state of the addressed data object. Theinvention further provides: a process component of the object stateengine, which defines vectors to subsets of object data (“theworkspace”) within the data matrix for dynamic information interchange;a processing component of the object state engine for handling externalquery submissions to the object; and a process component of the objectstate engine, which handles object-to-object query resultsynchronization. Each of the structures and processes described may beused separately or in combination.

[0170] The following examples are offered by way of illustration and notby way of limitation. In a typical laboratory collaboration example, ascientist acquires data from instrumentation and performs analysis onthese data. For calibration of the raw data, different protocols basedon the assay or method used are applied for such parameters like imagingdata (e.g. fluorescence intensity, optical density), molecularproperties (e.g. size, isoelectric point, net charge, melting point, 3Dstructure, subunit composition, amino acid composition, nucleotidecomposition), biological properties (e.g. enzyme activity, antibodyactivity), spectral properties (e.g. IR spectrum, UV spectrum, visiblespectrum, Raman spectrum, ESR spectrum, NMR spectrum). Additionally,data sets are annotated according to metabolic functions, location ongenes, sequencing information, and that like.

[0171] Within a group of researchers, typically each specialistgenerates sets of data from a specific instrument using a dedicatedtechnique and calibration method. Real-time collaboration however,requires access to the entire information of a single experiment, evenif subsets of data were generated at a different location and by adifferent research team. Secure access to such data is mandatory toprovide for confidentiality and selective use of information from suchdata.

[0172] In the access to data objects, timing is crucial, particularly inreal-time environments. To maintain object data consistency inmulti-user and stateless multi-network operations, a set of processes togovern activities on object level and prioritize actions based on timeavailability is mandatory. The described OSE performs this task.

[0173]FIG. 8 is a representation of a flow chart depicting processes ofthe object state engine (OSE). The central element of the OSE (bluepane) is the ALM process (orange), which governs any activity on objectlevel. The two state processing elements (in red) are query stateprocessing and object access processing, which handles routing (ORR),object-to-object interaction states, data information interchange (DII)definitions and workspace RDM vectors. The object state processing(green) includes storage of current state, history update functions,assignment of GLP/GMP-compliance via lookup table and ranking based onvalidation assessments. The outer pane (in green) represents theuniversal presentation layer (UPL), which contains non-time criticalcomponents for I/O operation and utilizes the state provided from theOSE for tasking. Object creation processes are only triggered by theOSE, but carried out within UPL tasking.

[0174]FIG. 9 is an example list of common state designations for lifescience applications. FIG. 9 depicts a representative portion of an IMOlookup table used in the life sciences. Actions are grouped inaccordance to GLP/GMP guidelines for certified and/or regulatedlaboratories. The list below contains only the most instructive examplesand is offered by way of illustration and not by way of limitation.

[0175]FIG. 10 is an example of an object state history, comprised oftime-sequential set of object activity records (OAR). FIG. 10 depicts anexample of the Object State History, comprised of OAR's (Object ActivityRecord). A typical record is shown from data object creation prior todata acquisition from an analytical instrument, several steps ofcalibrated analysis carried out by different users within and outsidethe local network. Note, that same state codes can occur within theobject state history for different users, e.g. output requests and thelike.

[0176] IV. Object Translation Engine for Intelligent Molecular ObjectData in Heterogenous Data Environments with Dynamic Application Needs

[0177] In the Object Translation Engine (OTE) aspect, structure, methodsand functions for real-time standardization, translation and integrationof intelligent molecular objects within heterogeneous data environmentsare provided.

[0178] These methods and functions comprise the following sets ofevent-driven processes: data information extraction and generation fornon-object data standardization; data type extraction to determine dataaccess and structure dependencies; provision of data type, access andstructure definition tables; database type extraction to determinedatabase access and structure dependencies; provision of database type,access and structure definition tables; application type extraction todetermine application type, access and structure; provision ofapplication type, access and structure definition tables; provision oftable lookup methods and functions to provide real-time translation ofintelligent molecular objects; real-time object property panepresentation to provide real-time integration according to defined datastructure, database, and application requirements.

[0179] In the event-driven data definition method, data object, datafield and raw data matrix definitions are determined by a componentwithin the translation engine, which is activated by an external accessand translation interface, which generates a set of processes todetermine data object, data field and raw data matrix definitions. Theseprocesses, similarly, extract the information required for data object,data field and raw data matrix definition of previously existing ornewly acquired data. Further, the processes extract also sets of tablesto generate corresponding property panes within the IntelligentMolecular Object.

[0180] In the event-driven standardization method, an external accessand translation interface component activates a component comprising ofa set of non-object data standardization processes. Thesestandardization processes extract the structure and functionalinformation required for standardization and normalization of non-objectdata, and provide information such as workspace definitions and the likerequired for standardization to external intelligent molecular objectstandardization components.

[0181] Simultaneously, in the event-driven data type extraction andtable definition methods, a component within the translation engine,which provides a set of processes to determine data access and structuredependencies, is activated by an external access and translationinterface. These processes extract the information required for datatype access and structure definition of previously existing or newlyacquired data, and direct the information to the data type definitioncomponent within the translation engine. The data type definitioncomponent then generates and provides a data type definition table,comprising structure and access definitions, to an external translationinterface component for intelligent molecular objects.

[0182] Simultaneously, in the event-driven database type extraction andtable definition methods, a component within the translation engine,which provides a set of processes for database type extraction, isactivated by an external access and translation interface. Theseprocesses determine database access and structure dependencies of datawithin heterogeneous databases, and direct the information to thedatabase type definition component. The database type definitioncomponent generates and provides a database type definition table,comprising structure and access definitions, to an external translationinterface component for intelligent molecular objects.

[0183] In the event-driven application type extraction and tabledefinition methods, a component within the translation engine, whichprovides a set of processes for application type extraction, isactivated by an external access and translation interface. Theseprocesses determine database access and structure dependencies ofheterogeneous applications, and direct the information to theapplication type definition component. The application type definitioncomponent then generates and provides an application type definitiontable, comprising structure and access definitions, to an externaltranslation interface component for intelligent molecular objects.

[0184] In the event-driven table lookup methods, a component within thetranslation engine, which provides a set of processes for table lookupto provide real-time translation within heterogeneous database andapplication environments, is activated by an external access andtranslation interface.

[0185] In the event-driven object pane description methods, a componentwithin the translation engine, which provides a set of processes forobject pane descriptors in real-time, according to defined datastructure, database, and application requirements within heterogeneousdatabase and application environments, is activated by an externalaccess and translation interface.

[0186] Methods and functions are provided, which define and describe thearchitecture for an object translation engine for intelligent molecularobject data. These methods and functions are comprised of sets ofevent-driven processes, which provide components for automated real-timedata standardization, translation and integration of intelligentmolecular objects within heterogeneous data environments.

[0187] The first component described herein, provides a set of processesto determine data object, data field and raw data matrix definitions.These definitions are required for data object, data field and raw datamatrix table definition and generation. This event-driven component isactivated by an external access and translation interface and directsextracted table information to a component for intelligent molecularobject property pane generation.

[0188] Next, a component described herein, provides a set of non-objectdata standardization processes. These processes extract the structureand functional information required for standardization andnormalization of non-object data. This event-driven component isactivated by an external access and translation interface and directsextracted information to external standardization components.

[0189] Next, a component described herein, provides a set of processes,which carry out data type extraction to determine data access andstructure dependencies. These data type definitions are required foraccess and structure definition table definition and generation. Thisevent-driven component is activated by an external access andtranslation interface and directs extracted table information to acomponent for generation of data type definition tables.

[0190] Next, a component described herein, provides a set of processesto generate data type, access and structure definition tables. Thesedata type definition tables are required for real time translation andintegration of intelligent molecular objects within diverse dataenvironments. This event-driven component is activated by the data type,access and structure extraction component, and directs extracted tableinformation to a component for intelligent molecular object propertypane generation.

[0191] Next, a component described herein, provides a set of processes,which carry out database type extraction to determine data access andstructure dependencies. These database type definitions are required foraccess and structure definition fable definition and generation. Thisevent-driven component is activated by an external access andtranslation interface and directs extracted table information to acomponent for generation of database type definition tables.

[0192] Next, a component described herein, provides a set of processesto generate database type, access and structure definition tables. Thesedatabase type definition tables are required for real time translationand integration of intelligent molecular objects within diverse dataenvironments. This event-driven component is activated by the databasetype, access and structure extraction component, and directs extractedtable information to a component for intelligent molecular objectproperty pane generation.

[0193] Next, a component described herein, provides a set of processes,which carry out application type extraction to determine data access andstructure dependencies. These application type definitions are requiredfor access and structure definition table definition and generation.This event-driven component is activated by an external access andtranslation interface and directs extracted table information to acomponent for generation of application type definition tables.

[0194] Next, a component described herein, provides a set of processesto generate application type, access and structure definition tables.These database type definition tables are required for real timetranslation and integration of intelligent molecular objects withindiverse data environments. This event-driven component is activated bythe application type, access and structure extraction component, anddirects extracted table information to a component for intelligentmolecular object property pane generation.

[0195] Next, a component described herein, provides a set of tablelookup processes, to provide real-time translation of the intelligentmolecular object within heterogeneous database and applicationenvironments. This event-driven component is activated by an externalaccess and translation interface, and directs provided table informationto a component for real-time molecular object property pane generation.

[0196] Finally, a component described herein, provides a set ofprocesses for object property pane presentation, to enable real-timeintegration of the intelligent molecular object, within heterogeneousdatabase and application environments. This event-driven component isactivated by an external access and translation interface, providesproperty pane presentation of the intelligent molecular object inreal-time, according to defined data structure, database, andapplication requirements.

[0197] Through provision of the methods and functions, the architectureis provided for the real-time translation and integration of intelligentmolecular objects within diverse data environments. It is evident fromthe above description that the methods and functions described allow forefficient real-time standardization, translation and integration ofcomplex, multidimensional, interdependent, heterogeneous data, withinheterogeneous database and applications environments.

[0198] In light of the description provided relative to the overallarchitectural platform and this additional detailed description, severalexemplary embodiments are now described for this aspect of the inventionby way of example, but not limitation.

[0199] In one aspect the invention provides an event driven sets ofprocesses, comprising an object translation engine to perform automatedreal-time data translation for integration of intelligent molecularobjects within heterogeneous data environments. It further provides acomponent within the translation engine to determine data object, datafield and raw data matrix definitions for intelligent molecular objectsand extracting sets of tables to generate corresponding property panes;as well as a component within the translation engine, which providesdata structure and functional information for standardization ofnon-object data; component within the translation engine to carry outdata type extraction to determine data access, structural and functionaldependencies for intelligent molecular objects; a component within thetranslation engine, which provides data type, access, structure andfunction definition tables for intelligent molecular objects; acomponent within the translation engine, which carries out database typeextraction to determine database access and structure dependencies forintelligent molecular objects; and a component within the translationengine, which provides database type, access and structure definitiontables for intelligent molecular objects. In addition, it provides acomponent within the translation engine, which carries out applicationtype extraction to determine application type, access and structure forintelligent molecular objects; component within the translation engine,which provides application type, access and structure definition tablesfor intelligent molecular objects; component within the translationengine, which provides table lookup to provide real-time translation ofthe intelligent molecular object within heterogeneous database andapplication environments; and, a component within the translationengine, which provides intelligent molecular object pane descriptors inreal-time, according to defined data structure, database, andapplication requirements. These components may be used separately or inany combination even though such combinations are not specificallydescribed here.

[0200] The following examples are offered by way of illustration and notby way of limitation.

[0201] In a typical example, several scientists perform analysis,utilizing data acquired via laboratory instrumentation, stored in alocal database and analyzed by a particular application or set ofapplications. Typically, each specialist generates sets of data from aspecific instrument using a dedicated technique and calibration methodand utilizes applications designed to access and interface with theparticular data type, access and structure definitions of the sets ofdata acquired.

[0202] Real-time analyses of the entire data resources relevant todiverse queries, however, require unified, real-time access to theglobal information relevant to diverse applications, even if subsets ofdata were generated at different locations, by different research teamsor using different methods. Further, these data subsets may be stored asdifferent data types, and according to differing access, structure anddatabase definitions.

[0203] Real-time analyses based on global data resources must addressstandardization, translation and integration requirements for diverseapplications in real-time, for high numbers of high-density data,according to heterogeneous data and database type, structure, and accessprotocols. In order for such analyses to occur, efficientworkspace-oriented means for standardizing, translating, and integratingsuch data must be provided. Using the described translation enginewithin the IMO platform, several scientists at different locations cannow efficiently perform simultaneous collaborative analysis on globaldata resources in real-time.

[0204]FIG. 11 is a representation of the unified presentation ofheterogeneous data within a query. The depiction below portrays theunified presentation of heterogeneous databases and data sets accessedin a representative experimental query. Different laboratory instrumentsare connected to different databases. In the query presented to theunified presentation layer, all these databases are in bi-directionalcommunication with the IMO's via the real-time Object Translation Engine(OTE), which, similarly, is interconnected directly to real-timeinstrumentation; thus a global query is performed on immediacy level.

[0205]FIG. 12 depicts the unified data presentation processing throughthe object translation engine for real-time analysis access. Thedepiction portrays the unified data presentation, processed by theobject translation engine and provided for analysis in real-time. Datadefinitions, structure, functions, database type and access definitionsand application definitions are processed via real-time lookup andobject pane descriptors.

[0206] V. Handling Device for Intelligent Molecular Object Data inHeterogenous Data Environments with High Density and DynamicApplications Needs.

[0207] In the Intelligent Object Handler aspect, structure and methodsare provided for: unified presentation and management of userdefinition, administration and security protocols; definition of userinteraction and computing environment protocols; and definition of datatype translation protocols.

[0208] Additional methods are provided for: real-time generation ofIntelligent Molecular Object (IMO) data; data object standardization;and definition of object representation for unified data management andanalysis in heterogeneous data environments with high data density anddynamic application needs.

[0209] In the presentation method, the unified presentation layer (UPL)provides the web-enabled graphical user interface that integrates thetechnology defined to unify diverse applications, laboratory systemsenvironments, and intelligent molecular object (IMO) data at the graphicuser interface layer. In the security and access method, the userdefinition and administration (UDA) shell prompts for user inputregarding access privileges environments at login. The master querycomponent (MQC) then presents security and access protocols to thepresentation layer and fields user queries and commands for dataacquisition, retrieval, or analysis.

[0210] In the environment definition method, the application/databasedefinition generator (ADG) interface handle dynamically detectsapplication and database requirements and defines the computingenvironment for the data type translator (DTT), the applicationframework (IMO-A), and the object handler (IMO-H).

[0211] In the object definition method, the data type translator (DTT)defines the data type dependencies for the intelligent molecular objectgenerator (IMO-G) and object handler (IMO-H) according to theapplications and database environment defined by theapplication/database definitions generator (ADG).

[0212] In the object creation method, the intelligent molecular objectgenerator (IMO-G) extracts relevant data information, routes real-timedata from ongoing data acquisitions and transforms device outputs andheterogeneous data types to intelligent molecular object (IMO) data.Next, the object standardization technique (IMO-ST) normalizes the databy calibration according to standardized empirical criteria.

[0213] In the representation method for integrated data management andanalysis, the application framework (IMO-A) provides integration andaccess protocols to heterogeneous applications and databases on theobject level. Simultaneously, the object handler (IMO-H) enablesreal-time management and analysis of intelligent molecular object (IMO)data through integrated meta-data tags and pointers called by and sentto the master query component (MQC) and presented via the unifiedpresentation layer (UPL).

[0214] Methods are provided to define and describe the architecture foruser interaction with and data handling of interactive, intelligentmolecular object (IMO) data.

[0215] A set of user interaction and environment definition protocolsare described comprising:

[0216] a unified presentation layer (UPL), which provides a web-enabledgraphical user interface to integrate components of other applicationsor devices;

[0217] a versatile, integrated handling tool to access and present theobject data within this user interface layer;

[0218] a user definition and administration (UDA) shell containingmechanisms to issue and regulate access privileges within the entity ofheterogeneous data network environments for the objects;

[0219] a master query component (MQC) which presents security and accessprotocol to the presentation layer and fields user queries and commandsfor data acquisition, retrieval, or analysis;

[0220] an application/database definition generator (ADG) to act as anautomated interface querying application and database requirements andto dynamically define the computing environment to generate the IMOdata; and,

[0221] a data type translator (DTT) module which automates the query ofapplication and database requirements and defines the data typedependencies for the intelligent molecular object generator describedabove.

[0222] Object representation definitions are provided, which govern datapreparation, data interaction and data presentation within differentobject layers to create state-relevant real-time updates in accordancewith generic data type conventions required by detected and/or userdefined applications, databases, and analytical environments.

[0223] These representations are comprised of:

[0224] an object generator which automates transformation of data fromlaboratory devices and/or heterogeneous data types into the intelligentmolecular object (IMO) data in real-time. Simultaneously, this objectgenerator refreshes and updates the object state history;

[0225] an object standardization technique comprised of a module whichautomates the normalization of data by calibration with standardizedempirical criteria;

[0226] an application framework for integration and access protocols toheterogeneous applications and databases on the object level; and,

[0227] an object handler which enables management of the intelligentmolecular object (IMO) data through integrated meta-data tag andpointers.

[0228] Through provision of the components and modules, real-time dataflow to and from the IMO data is completely described, governed,controlled, secured, monitored and data stream is minimized to providemeans for non-redundant, global and selective real-time querying andreporting.

[0229] It is evident from the above description, that this objectmanagement architecture allows for efficient real-time processing ofcomplex, multidimensional, interdependent queries by providing theinfrastructure on both, user-interface level and object-interactionlevel, to allow for a comprehensive analysis of otherwise inaccessible,inconsistent data sets.

[0230] In light of the description provided relative to the overallarchitectural platform and this additional detailed description, severalexemplary embodiments are now described for this aspect of the inventionby way of example, but not limitation.

[0231] In one aspect, the invention provides system, structure, andmethod for a set of user interaction, object and environment definitionprotocols for intelligent molecular objects (IMO). It also andalternatively provides a set of object representation definitionprotocols to prepare and present data objects for interaction withinheterogeneous environments, a Unified Presentation Layer (UPL) providinga web-enabled graphical user interface which integrates componentsand/or modules from diverse applications, laboratory systemsenvironments, and acts as handler for intelligent molecular object (IMO)data; a User Definition and Administration (A) shell to set up andgovern access privileges within heterogeneous data network environments;a Master Query Component (MQC) which presents security and accessprotocol to the presentation layer and fields user queries and commandsfor data acquisition, retrieval, or analysis; and anApplication/Database Definition Generator (ADG) interface whichautomates the query of application and database requirements and definesthe computing environment for the Data Type Translator (DTT), and theApplication Framework (IMO-A). This Data Type Translator (DTT) may befurther characterized to define the data type dependencies for theObject Generator (IMO-G) according to the applications and databaseenvironment defined by the Application/Database Definition Generator(ADG). The invention further provides an Object Generator (IMO-G) whichautomates transformation of heterogeneous data sources and types intoIntelligent Molecular Object (IMO) data in real-time. Simultaneously,this object generator refreshes and updates the object state history. Inanother aspect, the invention provides an Object StandardizationTechnique (IMO-S), which automates the normalization of data bycalibration with standardized empirical criteria; an ApplicationFramework (IMO-A) which provides integration and access protocols toheterogeneous applications and databases on the object level. An ObjectHandler (IMO-H), which enables management of Intelligent MolecularObject (IMO) data through integrated meta-data tag and pointers. Thesestructures, components, elements, and techniques, may be used separatelyor in any combination even though such combinations are not specificallydescribed here.

[0232] The following examples are offered by way of illustration and notby way of limitation.

[0233] Data from protein expression studies based on 2-dimensional gelelectrophoresis (2DE) are complex to interpret due to the limitedreproducibility of the experimental procedure, which typically does notallow for direct comparisons regarding spot position and quantity.Within the IMO technology, such object queries can be performed inreal-time at an individual spot level. The attached images of the userinterface handling input/output operation between the intelligentmolecular objects demonstrate the effective, interactive real-timeanswer generation process.

[0234]FIG. 13 is a representation of the unified graphical userinterface for IMO technology. The depiction is a representation of thegeneral graphical user interface for interaction with intelligentmolecular object (IMO) data. The dynamically defined menu bar showsextensible options in a standard order, consisting of, but not limitedto, drop-down menu items such as file, edit, view, options, objects,selection, query, analysis, link, user, window and help-functions.Within the common user interface window, several independent sub-windowsdefine the intelligent molecular objects, query and/or analysis toolsand the real-time answer window, which presents the relevant results intheir significance numerically and/or graphically.

[0235]FIG. 14 is a representation of a query dialog utilizing the IMOdata handling features. The depiction below is a representation of atypical query utilizing intelligent molecular object (IMO) technology.Such queries can be performed using pre-definable templates, subsets ofcommon, industry-specific questions, and/or by free form, user-definedentries.

[0236] VI. Data Pool Architecture for Intelligent Molecular Object Datain Heterogeneous Data Environments with High Data Density and DynamicApplication Needs

[0237] In the Intelligent Data Pool aspect of the invention, structureand methods are described herein for meta-data enhanced storage ofIntelligent Molecular Object (IMO) data within defined intra-poolsubsets. Methods are provided for: pool boundary protocol definitions;meta-data query definitions; and pool content access definitions.

[0238] In the pool boundary protocol method, the intra-pool securityauthentication (iPSA) module authenticates intra-pool data requestsaccording to user login and object data identification. Next, theintra-pool availability monitor (iPAM) and intra-pool exchange protocol(iPEP) presents intra-pool relationships and availability to theauthenticated user. Simultaneously, the object integrity assessment(OIA) module assesses object integrity for security and qualityassurance/quality control and the intra-pool integrity assessment (iPIA)module assesses data integrity within defined intra-pools for securityand quality assurance/quality control.

[0239] In the meta-data query method, the real-time meta-data link (RML)component provides for rapid relevant data access based on queryparameters and global object meta-data index (MDX) content.Simultaneously, the object-to-object query (OQM) component provides forrapid query optimization based on data object intercommunicationregarding query parameters and global object meta-data index (MDX)content. Depending on query parameters, an iPool-to-iPool Query (PPQ)component may be called, which provides for query optimization based onintra-pool data intercommunication regarding query parameters and globalobject meta-data index (MDX) content contained within more than oneintelligent object intra-pool (IOP).

[0240] In the pool content access method, the aggregate meta-data indexgenerator (aMDX) provides for meta-data index generation of aggregatedintelligent molecular object meta-data, based on query parameters.Simultaneously, the aggregate real-time significance generator (aRSG)provides for significance detection of values located within the globaldata pool based on query parameters and global object meta-data index(MDX) content. Next, the object property-selective pre-sorting tool (IMOZoomer) organizes meta-data index based object relationships withinindividual iPools to allow for real-time result aggregation and viewingand real-time exclusion of irrelevant object data layers. In a furtheraspect, these structures, methods, and functions operate in synergisticmanner to provide advantageous query and retrieval operations andprovide a business method and operating model for accessing complexbiological, life science, chemical, and other bioinformaticsinformation.

[0241] Data Pool architecture and methods are provided to define anddescribe a meta-data enhanced organization structure for IntelligentMolecular Object (IMO) data relationships and analytical resourceaccessibility.

[0242] The data pool boundary methods and definitions described hereinprovide security-,boundary-and integrity-protocols for secure access toand integration of global and/or local data pools.

[0243] A set of pool boundary protocols are provided, comprising of:

[0244] an iPool Security Authentication (iPSA) module, whichauthenticates and permits or rejects intra-pool data requests accordingto user login and object data identification;

[0245] an iPool Availability Monitor (iPAM) and an iPool ExchangeProtocol (iPEP) which governs intra-pool relationships and supportsaccess and exchange commands;

[0246] an Object Integrity Assessment (OIA) module which assesses objectintegrity for security and quality assurance/quality control and whichprovides alerts regarding object validation status;

[0247] an iPool Integrity Assessment (iPIA) module which assesses dataintegrity within a defined intra-pool for security and qualityassurance/quality control and which provides alerts regarding iPoolvalidation status.

[0248] The data pool architecture and methods defined herein enableIntelligent Molecular Objects (IMOs) to communicate via active objectalgorithms, which include, but are not limited to, automated meta-dataindexing, object-to-object query and intra-pool-to-intra-pool queryprotocols.

[0249] A set of data pool query protocols are provided, comprising of:

[0250] a Real-time Meta-data Link (RML) component which provides forrapid relevant data access based on query parameters and objectmeta-data index (MDX) content;

[0251] an Object-to-Object Query (OQM) component which provides forquery optimization and parallel processing based on data objectintercommunication regarding query parameters and global objectmeta-data index (MDX) content;

[0252] an iPool-to-iPool Query (PPQ) component which provides forparallel processing and query optimization based on intra-pool dataintercommunication regarding query parameters and global objectmeta-data index (MDX) content contained within more than one intelligentobject intra-pool (IOP).

[0253] The data pool architecture and methods defined herein providecontent access and presentation definitions for significance detection,result aggregation and results generation.

[0254] Further, data pool content access and presentation protocols areprovided, comprising of:

[0255] an Aggregate Meta-data Index Generator (aMDX) which provides formeta-data index generation of aggregated intelligent molecular objectmeta-data, based on query parameters;

[0256] an Aggregate Real-time Significance Generator (aRSG) whichprovides for significance detection of values located within the globaldata pool based on query parameters and global object meta-data index(MDX) content;

[0257] an object property-selective pre-sorting tool, the IMO Zoomer,which organizes meta-data index based object relationships withinindividual iPools to allow for real-time result aggregation andreal-time exclusion of irrelevant object data layers.

[0258] Through provision of the architecture, methods, and modules, theinfrastructure is provided for secure, unified object storage andobject-to-object and intra-pool-to-intra-pool query-based interaction,to allow for a comprehensive real-time analysis of otherwiseinaccessible, inconsistent data sets.

[0259] It is evident from the above description, that the data poolarchitecture and methods described above allow for efficient real-timeprocessing of terabytes of complex, multidimensional, interdependentdata, thereby providing real-time answers to queries withinheterogeneous data environments with high data density and dynamicapplication needs.

[0260] In light of the description provided relative to the overallarchitectural platform and this additional detailed description, severalexemplary embodiments are now described for this aspect of the inventionby way of example, but not limitation.

[0261] In one aspect, the invention provides system, architecture,structure, and method for an Intelligent Object Pool (IOP). This IOP maybe further defined to include subsets of Intra-Pools (iPools) forIntelligent Molecular Object (IMO) data architecture. In another aspect,the invention provides a Set of Pool Boundary Protocol definitions,describing boundaries, integrity and persistence of IntelligentMolecular Object (IMO) relationships. In another aspect, the inventionprovides a Set of Meta-data Query definitions, consisting of, but notrestricted to, interactive presorting and exclusion algorithms, objectclustering, a meta-data linking component, and object-to-objectinteraction definitions. In another aspect, the invention provides a Setof Pool Content Access definitions, consisting of, but not restrictedto, object-to-analysis tools interactions, result merging algorithms,learning algorithms and a real-time answer generator. In another aspect,the invention provides a Pool Boundary Protocol definition, consistingof an iPool Security Authentication (iPSA) module to authenticateintra-pool data requests according to user login and object dataidentification. In yet another aspect, the invention provides a PoolBoundary Protocol definition, consisting of an iPool AvailabilityMonitor (iPAM) and an iPool Exchange Protocol (iPEP), which governintra-pool relationships. In still another aspect, the inventionprovides a Pool Boundary Protocol definition, consisting of an ObjectIntegrity Assessment (OIA) module to assess object integrity forsecurity and quality assurance/quality control. In even still anotherembodiment, the invention provides a Pool Boundary Protocol definition,consisting of an iPool Integrity Assessment (iPIA) module to assess dataintegrity within a defined intra-pool for security and qualityassurance/quality control. In a further embodiment, the inventionprovides a Meta-data Query definition, consisting of a Real-timeMeta-data Link (RML) component, which provides for rapid relevant dataaccess based on query parameters and global object meta-data index (MDX)content. In one embodiment, the Meta-data Query definition, comprises anObject-to-Object Query (OQM) component, which provides for rapid queryoptimization based on data object intercommunication regarding queryparameters and object meta-data index (MDX) content. In the same or adifferent embodiment, the Meta-data Query definition, comprises aniPool-to-iPool Query (PPQ) component, which provides for queryoptimization based on intra-pool data intercommunication regarding queryparameters and global object meta-data index (MDX) content containedwithin more than one intelligent object intra-pool (IOP). The inventionfurther provides a Pool Content Access definition, consisting of anAggregate Meta-data Index Generator (aMDX), which provides for meta-dataindex generation of aggregated intelligent molecular object meta-data,based on query parameters; a Pool Content Access definition, consistingof an Aggregate Real-time Significance Generator (aRSG), which providesfor significance detection of values located within the global data poolbased on query parameters and global object meta-data index (MDX)content; and, a iPool Content Order definition, consisting of an objectproperty-selective pre-sorting tool, the IMO Zoomer, which organizesmeta-data index based object relationships within individual iPools toallow for real-time result aggregation and real-time exclusion ofirrelevant object data layers. These structures, components, elements,definitions, techniques, and the like may be used separately or in anycombination even though such combinations are not specifically describedhere.

[0262] The following examples are offered by way of illustration and notby way of limitation.

[0263] Data from a local subset (intra-pool, iPool) of IntelligentMolecular Objects (IMOs) were queried against specific proteinexpressions based on 2-dimensional gel electrophoresis (2DE) data.During the real-time answer-finding process, object-to-objectinteractions are represented via a graphical iPool Viewer, which alsoaccesses relevancy of individual result contributions to generate aunique, exact, relevant real-time answer.

[0264]FIG. 15 depicts a representation of the process model for theintelligent molecular object pool (COP). The depiction represents theprocess model for the intelligent molecular object pool (IOP). Data froma global data resource are passed through an access interface consistingof a security layer, a set of access and/or exchange protocols andintegrity assessment procedures onto the intelligent molecular objects(IMO). The pathways involved in unified IMO data interaction to lastlygenerate the real-time answer and pass it back through security to theobject handler for output are outlined in the diagram.

[0265]FIG. 16 depicts a chart representation of intra-pool (iPool)relationships and intelligent molecular object (IMO) relationshipswithin the iPool. In a global, heterogeneous environment, data fromdiversified sources are governed by access definition protocols to allowfor dynamic data exchange. The chart below depicts those relationship onan intra-pool (iPool) level and the access definition for individualintelligent molecular objects (IMOs) within the iPool and public and/orweb-based global data sources. The upper part (in yellow-red) of thediagram depicts data within intranets, LANs and the like, while thelower, larger part (blueish-grey in the color figures) of the diagramcontains several different forms of public/web-accessible data sources.

[0266]FIG. 17 (FIG. 17A, FIG. 17B, FIG. 17C) depicts a set of GUI screenrepresentations within the unified presentation layer (UPL) concept,showing a graphical view of object intra-pools and their data subsetsand a dendrogram representation of dependencies and similarities ofobject properties based on meta-data indexed results. The depiction is arepresentation of the graphical user interface window within the unifiedpresentation layer (upper smaller image) displaying the intra-poolrelationships, the iPool Viewer (lower detail window image).Interactions between individual intelligent molecular object (IMO) datawithin the set of objects are outlined in the upper part of the display.Query-relevant object interactions are depicted in green, those withlower confidence level in blue and such objects, which are irrelevant tothe query within the result-finding process are shown in red. The lowerpart of the window includes graphical (left side) and numerical (rightside) summary information about the iPool objects contributions.

[0267] Operating and Business Model Providing Information Services

[0268] Among its inventive aspects, the invention provides arevolutionary new information technology platform that places the power(in terms of response time to complex queries and analytical requestsutilizing current tools, such as a common query in bioinformatics fordetection of spots in a 2-D Electrophoresis gel) of an entire floor ofclustered servers or ‘massively parallel mainframe’ computers (e.g. IBM,COMPAQ, or the like) at the hands of any scientist or consumer, for thatmatter, with a computer and a connection to the web. As a result,information processing, management and storage in every field imaginable(Life Sciences, Agribusiness, Large Scale Manufacturing, PhysicsImaging, and many more) are dramatically and revolutionarily moreefficient and cost effective.

[0269] The inventive system, method, and business model is projectedtoward an initial market in the Life Sciences industries as a result ofinternal expertise and a tremendous and growing need for the kind oftime efficiency and cost effectiveness that our IT Platform willprovide.

[0270] To further facilitate the need of Life Science and LifeScientist, the invention provides developments and advances toward anumber of product modules (typically implemented as computer programsoftware for execution on computer systems) ranging from Drug Discovery,Genomics, Proteomics to Metabolism product modules, that will resideupon the platform and thereby enable the dramatic shortening oftimelines for new drug development and gene therapies (while alsoproviding for rapidly, validated diagnosis and treatment) in a Real-Timeand cost effective manner. The abbreviated timelines will, in turn,provide cost savings for each new drug to the tune of at least $200million dollars, while facilitating sales, based on earlier thanexpected market entry, upwards of $2 billion, for each new drug.

[0271] These IT platforms will become a standard, particularly aspurveyors of solutions for substantially improved drug discovery, viaits various Drug Discovery, Genomic and Proteomic product modules.

[0272] The motivation for the platform architecture and its associatedmethods and procedures has arisen largely because, as a result of thehuman genome project and other related activities (genomics andproteomics), Biotech and Pharmaceutical companies are drowning in aflood of information, information which may hold the key to powerful andvaluable new drug discoveries and gene therapies.

[0273] Currently, Biotechology and Pharmaceutical companies are spendingupwards of $40 billion each year to sift through this information inorder to uncover new drug candidates and potential gene therapies.Despite the vast sums of money being spent, the task of finding new drugcandidates and gene therapies remains daunting, costly and highlyinefficient.

[0274] Some reasons for this can be traced to a number of factors,several of which include: a variety of different types and kinds ofdatabases; applications and systems that cannot communicate with oneanother; the enormous cost to retool a company's existing informationtechnology platform; the scarcity of bioinformatics specialist; and, thelack of appropriate analysis tools.

[0275] As a result, Biotechnology and Pharmaceutical companies arefacing three critical issues. The pressure to reduce cost, to speed upthe entire process for new drug development and to recover R&D cost morequickly via the sales of new drugs. To date, this remains a whollyunrealized goal.

[0276] As a part of the solution, the inventive IMO IT platform providesBiotech and pharmaceutical companies with the ability to quickly andcost effectively sort through the growing mass of information todiscover and produce drugs in vastly reduced time periods and at greatlyreduced cost. It will be possible as a result of the IMO™ IT platformand drug discovery, proteomics and genomics modules for Biotech andPharmaceutical companies to shorten the drug discovery process by 2 to 4years and save upwards of $200 million. Additionally, the variousBiotech and Pharmaceutical companies will benefit from earlier thanexpected revenues (several billion dollars), as a result of reduceddevelopment time and thus earlier than anticipated market entry for eachnew drug.

[0277] The inventive system and methods therefore also provide orsupport a number of new and novel business model and operating modelinnovations that satisfy the needs of the information community as wellas provide revenue. Forming corporate strategic relationships are partof this overall concept.

[0278] Business development efforts related to the inventive technologyinclude marketing the inventive products and services to Biotech andPharmaceutical research companies initially, and to Life Sciencecompanies, in general.

[0279] Heretofore, the major participants in the field of Biotechnologysoftware for data analysis have comprised the following threecategories: Legacy Data Warehouses, data marts, ERP data mining toolcompanies, which provide proprietary applications and databases;Applications Service Providers (ASPs), Portals and other web-enabledservice providers; and Network Integration Providers, which providenetwork integration of public databases, proprietary data andapplications as well as support for local/remote collaboration anddecision-making.

[0280] These established companies, have been, in general, committed tolegacy software, narrowly useful web-based technology, or piecemealcomponent-based integration solutions, which have depended and continueto depend on expensive mainframe, server cluster, and hardware-enabled“parallel processing” computing to provide their analytical product.

[0281] As of yet, no clear leader has emerged to meet the demand forinnovative software solutions within this rapidly expanding field, andtherefore there remains a need for a more innovative and satisfactorysolution.

[0282] Embodiments of the inventive system, method, and business modelwill generate revenue from, for example, at least one or more of thefollowing areas; (1) the sale and licensing of its IT Platform, (2) thesale of its various Drug Development, Genomics, Cheminformatics andProteomics modules, (3) the sale and licensing of its data-pool assets,(4) royalties from strategic collaborations, and (5) internal use of theIT Platform for production of valued information such as for internaldrug discovery or monitoring of such as public health data. Otherrevenue streams are also contemplated.

[0283] Several exemplary application areas are now described by way ofexample. While the above referenced related patent applications havedescribed innovations in information technology, especially forprocessing of high numbers of heterogeneous high-density data inheterogeneous computing environments, and more particularly inbiotechnology, pharmaceutical, chemical, and life science environments,the invention is not so limited. The systems, methods, interfaces,engines, procedures, functions, algorithms, and other aspects of theinvention as described here and in the related applications that areincorporated by reference may advantageously be applied to and/or usedin conjunction with information systems generally, physics imaging andanalysis, intelligence integration and analysis, large scalemanufacturing, agriculture and agribusiness, geographic informationsystems (GIS), the food industry, epidemiology, large scale forensics,economics and financial systems, health and human services, medicalsystems, as well as many other fields in which large amounts of data areinvolved.

[0284] In the field of Information Systems, applications of theinventive structure and method include but are not limited toInformation Technology (IT) Platform(s), B2A infrastructure, databasetechnology, and platform back-ends, among others. Some of the value inthis area includes but is not limited to Flexible, Efficient, andScalable Systems Integration; Data-enabling for Fast and Secure DataAccess and Management; and Scalable and Efficient ApplicationsDevelopment Environment. Computer, network, and information systemsproviders may benefit from aspects of the invention.

[0285] In the field of Physics Imaging and Analysis, applications of theinventive structure and method include but are not limited toGroundwater, Oil, Mineral Exploration, Mining, Mapping, and Real-timeAnalysis. Some of the value in this area includes but is not limited toAdded Efficiency and Functionality for Remote, Magnetic and SonicImaging and Analysis, Reduced Exploration Costs, and IncreasedPredictive Accuracy for Reduced Extraction Footprint. Organizations suchas NASA, the Department of Energy, an mineral and resource explorationorganizations may benefit from aspects of the invention.

[0286] In the field of Large Scale Manufacturing, applications of theinventive structure and method include but are not limited toJust-in-time (JIT) Inventory Management, Process Management, Robotics,and CAD/CAM. Some of the value in this area includes but is not limitedto Improved Market, Acquisition and Inventory based on Global DataAccess, Flexible and Scalable Process and Infrastructure Management,Real-time, and Integrated Process Optimization. Automobilemanufacturers, chemical manufacturers, semiconductor manufacturers, andother large scale material and manufacturing organizations may benefitfrom the inventive technology.

[0287] In the field of Agribusiness, applications of the inventivestructure and method include but are not limited to GMO's, CropEngineering, Seed Banks and Animal Breeding. Some of the value in thisarea includes but is not limited to Enhanced BioengineeringApplications, Automated QA/QC, Integrated GLP/GMP, Inventory and ProcessFlow Automation, and Real-time Supply Chain Management. Chemical,textile, and other food research and production organizations maybenefit from the inventive technology in this area.

[0288] In the Food Industry, applications of the inventive structure andmethod include but are not limited to Modified Additives, FoodInstantization, Food and Foodstuffs processing, Manufacturing ProcessDesign and Automation, and Inventory and Product Distribution. Some ofthe value in this area includes but is not limited to EnhancedBioengineering Applications, Automated QA/QC, Integrated GLP/GMP,Inventory and Process Flow Automation, and Real-time Supply ChainManagement, among others. Consumer food producers, processors, andpackagers will benefit from such technology.

[0289] In the field of Epidemiology, applications of the inventivestructure and method include but are not limited to Disease Studies,toxicology studies and analysis, and disease Outbreak Prevention. Someof the value in this area includes but is not limited to its Real-timecapabilities, and its ability to provide Predictive Modules forMultidimensional Disease Studies and Diagnostics. For example, theCenter for Disease control (CDC), the Department of Health and HumanServices (DHHS), and various governmental and environmental laboratoriesmay benefit from such technology.

[0290] In the field of forensics, particularly Large Scale Forensics,applications of the inventive structure and method include but are notlimited to Fingerprint, DNA, and Materials Analysis, and Real-time DataIntegration and Access. Some of the value in this area includes but isnot limited to Real-time Access to Global Data Records, On-siteFingerprint, Photo Searching, and DNA matching. Law enforcement agenciessuch as the FBI, Interpol, and other investigative and law enforcementagencies will benefit from the technology, and in addition suchorganizations such as insurance companies and health maintenanceorganizations will benefit.

[0291] Therefore it will be appreciated that the invention is notlimited to any particular field or application; rather, aspects of theinvention may be applied to information technology generally where largeamounts of heterogeneous data or information are involved.

[0292] Further Embodiments

[0293] Numerous embodiments have been described for several differentaspect of the invention. We now collect and highlight selected ones ofthese embodiments that have particular significance, though nonenecessarily represents the preferred embodiment, and the elementsdescribed therein may be combined in different ways than as recited inthese particular embodiments:

[0294] (1) A software architecture for an information technologyplatform, comprising of always-on and event-driven, engines, interfacesand processes and using intelligent molecular software data objects forinteractive data records.

[0295] (2) The architecture in (1), further comprising:

[0296] a. an Intelligent Molecular Object (IMO), a versatile,data-enabling software object, which provides for real-time translation,integration, and object-to-object/object-to-analysis tools communicationat the object data level, to allow multidimensional,platform-independent complex queries in real-time;

[0297] b. an Intelligent Object Handler (IOH), which provides theapplication framework and user interface for IMO data, to allow forseamless integration of their benefits into legacy systems; and

[0298] c. an Intelligent Object Pool (IOP), comprising one globalvirtual data pool comprised of IMO data, which integrates diverse dataresources on any system or network to provide result aggregation andinstant answers across diversified data subsets.

[0299] (3) The architecture in (2), wherein the IMO is further comprisedof:

[0300] a. a unique identifier (UID), comprising a property pane layercreated at IMO generation, which provides typically a 10 byte,alphanumeric unique identification on any system or network;

[0301] b. an object access manager (OAM), a property pane layer whichgoverns data security and access according to UID permissions;

[0302] c. an object root router (ORR), a property pane layer whichcontains information to define the origin of the object within thesystem or network;

[0303] d. an interactive content router (ICR), a property pane layerwhich routes content and results interactively across the system ornetwork;

[0304] e. a status management component (SMC), comprised of an objectstate engine and certain interfaces, which monitors data integrity andcommand history in GLP/GMP-compliance via state history and governstable lookup actions via the ICR;

[0305] f. a property pane controller (PPC), which controls theinitiation of IMO communication according to activation by elements 3 athrough 3 d, above;

[0306] g. vector subsets (VSS) for automatic, dynamic, or user-definedworkspace definitions, which provide vectorized, direct addressing ofdata subsets for the ICR to minimize network traffic;

[0307] h. meta-data indices (MDX), to provide efficient access viadynamically updated meta-data description relevant to extant dataqueries and definitions;

[0308] i. object pane descriptors (OPD), which provide information abouteach object property pane and their function as required for directcommunication with diversified applications and databases;

[0309] j. an interface for direct information interchange (DII), whichprovides the interface to communication at the object level;

[0310] k. an application translator link (ATL), which activates the OAMand ICR to determine the property panes for functional presentation andaccess within a given application or database environment;

[0311] l. an object graph preview (OGP) pane, comprising a limitedresolution image and graphics viewer for quick graphical data review,particularly of image data and spectral datasets;

[0312] m. a raw data matrix (RDM), comprising a property pane whichprovides the full information subset for any data format or structure;and,

[0313] n. matrix structure definitions (MSD), which allows for datafield mapping and enables vector access to specific data fields.

[0314] (4) The architecture in (2), wherein the IOH further comprises:

[0315] a. a unified presentation layer (UPL), which provides aweb-enabled graphical user interface (GUI) to integrate componentsand/or modules from diverse applications, laboratory systemsenvironments and to act as handler for IMO data;

[0316] b. a user definition administration shell (UDA), which sets upsand governs access privileges to individual IMO data at the user-definedlevel and is accessible within heterogeneous network environments;

[0317] c. at least one engine for data object normalization andstandardization, image normalization and standardization, IMO datatranslation, distributed learning, and knowledge extraction;

[0318] d. at least one access interface to and in-between instruments,data and applications, comprising interfaces which include, but are notlimited to, direct instrument acquisition and control, applicationtranslation, direct object query, result generation, and legacysynchronization;

[0319] e. a master query component (MQC), create complex,multidimensional queries, containing pre-defined, configurable subsetsof forms commonly used, but not restricted to, in diverse areas of LifeSciences;

[0320] f. an IMO generator (IMO-G), an event-driven component to acquiredata from heterogeneous data resources, including from ongoing dataacquisition, in real-time and transforms device outputs andheterogeneous data types to IMO data;

[0321] g. an IMO handle (IMO-H), which enables user management of IMOdata utilizing integrated meta-data tags and pointers;

[0322] h. an IMO application framework (IMO-A), which providesintegration and access protocols to heterogeneous applications anddatabases on the object level;

[0323] i. an application definition generator (ADG), which automates thequery and generation of application and defines computing environmentsfor the IMO data translation;

[0324] j. at least one data type translator (DTT), which define the datatype dependencies for the IMO-G according to the applications anddatabase environments defined by the ADG; and

[0325] k. an automated application assembly component (AAA), whichprovides for just-in-time (JIT) module linking.

[0326] (5) The architecture in (2), wherein the IOP further comprises:

[0327] a. sets of Intra-Pools (iPools), regulated by boundary protocols,which provide data subset management and the define integrity andpersistence of IMO relationships;

[0328] b. iPool security authentication protocols (iPSA), whichauthenticates iPool data requests according to user login and objectdata identification;

[0329] c. iPool availability monitoring protocols (iPAM), which definethe iPool availability and access requirements of diverse data subsets;

[0330] d. iPool exchange protocols (iPEP), which determine and governiPool data exchange protocols according to user-defined criteria;

[0331] e. an object integrity assessment component (OIA), which assessobject integrity for security and QA/QC;

[0332] f. sets of engines and interfaces to access and generate rankedresults within the IOP, including but not limited to an integrityassessment interface, a real-time meta-data linking interface and aniPool-to-iPool query interface;

[0333] g. an iPool meta-data index (iMDX), which provides dynamic,automated, and user-defined meta-data indices at the iPool level;

[0334] h. an aggregate meta-data index (aMDX), which provides dynamic,automated, and user-defined meta-data indices at the aggregate IMOlevel, inclusive of all relevant data resources;

[0335] i. an object-to-object query meta-data sorter (OQM), to generatetemporary tables based on dynamic, automated, and user-defined meta-dataindices; and

[0336] j. an aggregate real-time significance generator (aRSG), whichprovides for significance detection of values based on query parameters,meta-data indices when relevant, and IMO data ranking.

[0337] (6) The architecture in (4), wherein the engines furthercomprise:

[0338] a. an object state engine (OSE), which provides acontinuously-running (always on) set of processes, which monitor andgovern activities of IMO data, performing real-time recording, updatingand logging functions in GLP/GMP-compliant format.

[0339] (7) The architecture in (4), wherein the engines furthercomprise:

[0340] a. a set of IMO standardization techniques (IMO-S), comprisingengines which provide algorithms for tracking, standardization and/ornormalization of object data;

[0341] b. an generic object normalization engine (ONE), which extractsvariable and non-variable regions within any set of object data andgenerates a global standard to which all data can be referred;

[0342] c. an engine for global image normalization (GIN), which extractsvariable and non-variable regions within any set of image data andgenerates a global standard to which all data can be referred;

[0343] d. an object translation engine (OTE), which is comprised ofmethods and functions for real-time meta-data extraction and tablegeneration of raw data matrix, data object, data field, data structure,data functional information, data type, database type, and applicationtype definitions for the OPD;

[0344] e. a distributed learning engine (DLE), which provides algorithmsfor dynamic, automated, and user-defined hypothesis generation utilizingglobal data resources; and

[0345] f. a knowledge extraction engine (KEE), which provides algorithmsfor dynamic, automated, and user-defined significance discovery andreport generation.

[0346] (8) The architecture in (5), wherein the engines furthercomprise:

[0347] a. a result aggregation engine (RAE), to validate, assemble, rankand tabulate results passed from the IOH and to generate output reportsacross diversified data subsets.

[0348] (9) The architecture in (3), wherein the interfaces furthercomprise:

[0349] a. a direct information interchange interface (DII), which allowsfor rapid analysis and results aggregation by providing the interfacefor object-to-object and object-to-analysis tools via such relatedinterfaces and engines including, but not limited to the OQI, OTE, andthe DLE.

[0350] (10) The architecture in (4), wherein the interfaces furthercomprise:

[0351] a. a graphical user interface (GUI), utilizing web-enablingstandards including but not limited to Java and XML;

[0352] b. a direct instrument acquisition and control interface (DIAC),which provides bi-directional real-time communication between the IOH,the IMO and diverse instrumentation;

[0353] c. an application translation interface (ATI), to provideautomated real-time detection of diverse data and applications and gatebi-directional access to the OTE, thus enabling functional, standardizedintegration of IMO data within heterogeneous data and applicationsenvironments;

[0354] d. an object query interface (OQI), comprising an interface fordirect information interchange (DII) with IMO data, which initiatesquery analysis and results aggregation;

[0355] e. a result generation interface (RGI) ) to provide validated,assembled, ranked and tabulated results to the RAE, thus enabling thegeneration of output reports across diversified data subsets; and

[0356] f. a legacy synchronization interface (LSI), to providepersistence and synchronization of offline legacy data.

[0357] (11) The architecture in (4), wherein the interfaces furthercomprise:

[0358] a. an iPool integrity assessment interface (iPIAi), to asses dataintegrity within a defined iPool for security and QA/QC;

[0359] b. a real-time meta-data link interface (RML), which provides forrapid relevant data access based on query parameters and MDXinformation;

[0360] c. a pool-to-pool query interface (PPQ), which provides for queryoptimization based on query parameters and relevant iPool data andmeta-data intercommunication; and,

[0361] d. an IMO Zoomer (IMO-Z), which defines proximity and functionalranking of individual IMO data within the IOP and enablesmultidimensional IMO data viewing to represent object relationshipswithin the pool and in relationship to other iPools.

[0362] (12) An Architecture using interactive Objects for real-time,efficient, multidimensional, interdependent intelligent queries.

[0363] (13) An Intelligent Object comprising of a set of functionallayers (“Panes”).

[0364] (14) A methods for creating the Intelligent Objects.

[0365] (15) A Unique Object Identifier (US) Pane within the object,which identifies each object and contains rules for object data securityand access permissions.

[0366] (16) An Object Root Router (ORR) Pane within the object, whichdefines the origin of the object within the network.

[0367] (17) An Interactive Content Router (ICR) Pane within the object,which defines where content and/or results will be directed within thenetwork.

[0368] (18) A Status Management Component (SMC) Pane within the object,which monitors data integrity and command history in G*P-compliantLIMS-style.

[0369] (19) A Meta-Data Index (MDX) Pane within the object.

[0370] (20) An Object Pane Descriptor (OPD) within the object, whichincludes an Application/Database Definition Router (ADDR).

[0371] (21) An Application Translator Link (ATL) Pane within the object,which includes an Object Access Manager (OAM) for applicationintegration.

[0372] (22) An Object Query Interface (OQI) for Object-to-Object DirectInformation Interchange (DII).

[0373] (23) An Object Graph Preview (OGP) Pane within the objectincluding a limited resolution image/graphics viewer for quick graphicaldata review.

[0374] (24) A Raw Data Matrix (RDM) Pane within the object including aMatrix Structure Descriptor (MSD).

[0375] (25) A continuously-running set of processes, comprising anobject state engine monitoring and governing any activities ofintelligent molecular objects in real-time.

[0376] (26) A process component of the object state engine to trigger amodule for creating an object if such object does not exist, andassigning a unique identifier to it.

[0377] (27) A set of process components within the object state engine,which monitor object activities or transactions with the object andrecord its activity history.

[0378] (28) A process component of the object state engine, whichrelates activities to Good Laboratory Practices/Good ManufacturingPractices (GLP/GMP)-compliant, laboratory information management system(LIMS)-style experiment data states and validates the current action byassigning a defined state to the object.

[0379] (29) A process component of the object state engine, whichgoverns access to the object and object-to-object activities based onsecurity protocols and privilege definitions.

[0380] (30) A process component of the object state engine, whichmaintains status remembering in state-less networks and transmits actionconsequences back to the backend system.

[0381] (31) A process component of the object state engine, which ranksrequests for information exchange based on annotation or validationstate of the addressed data object.

[0382] (32) A process component of the object state engine, whichdefines vectors to subsets of object data (“the workspace”) within thedata matrix for dynamic information interchange.

[0383] (33) A processing component of the object state engine forhandling external query submissions to the object.

[0384] (34) A process component of the object state engine, whichhandles object-to-object query result synchronization.

[0385] (35) Event driven sets of processes, comprising an objecttranslation engine to perform automated real-time data translation forintegration of intelligent molecular objects within heterogeneous dataenvironments.

[0386] (36) A component within the translation engine to determine dataobject, data field and raw data matrix definitions for intelligentmolecular objects and extracting sets of tables to generatecorresponding property panes.

[0387] (37) A component within the translation engine, which providesdata structure and functional information for standardization ofnon-object data.

[0388] (38) A component within the translation engine to carry out datatype extraction to determine data access, structural and functionaldependencies for intelligent molecular objects.

[0389] (39) A component within the translation engine, which providesdata type, access, structure and function definition tables forintelligent molecular objects.

[0390] (40) A component within the translation engine, which carries outdatabase type extraction to determine database access and structuredependencies for intelligent molecular objects.

[0391] (41) A component within the translation engine, which providesdatabase type, access and structure definition tables for intelligentmolecular objects.

[0392] (42) A component within the translation engine, which carries outapplication type extraction to determine application type, access andstructure for intelligent molecular objects.

[0393] (43) A component within the translation engine, which providesapplication type, access and structure definition tables for intelligentmolecular objects.

[0394] (44) A component within the translation engine, which providestable lookup to provide real-time translation of the intelligentmolecular object within heterogeneous database and applicationenvironments.

[0395] (45) A component within the translation engine, which providesintelligent molecular object pane descriptors in real-time, according todefined data structure, database, and application requirements.

[0396] (46) A set of user interaction, object and environment definitionprotocols for intelligent molecular objects (IMO).

[0397] (47) A set of object representation definition protocols toprepare and present data objects for interaction within heterogeneousenvironments.

[0398] (48) A Unified Presentation Layer (UPL) providing a web-enabledgraphical user interface which integrates components and/or modules fromdiverse applications, laboratory systems environments, and acts ashandler for intelligent molecular object (IMO) data.

[0399] (49) A User Definition and Administration (UDA) shell to set upand govern access privileges within heterogeneous data networkenvironments.

[0400] (50) A Master Query Component (MQC) which presents security andaccess protocol to the presentation layer and fields user queries andcommands for data acquisition, retrieval, or analysis.

[0401] (51) An Application/Database Definition Generator (ADG) interfacewhich automates the query of application and database requirements anddefines the computing environment for the Data Type Translator (DTT),and the Application Framework (IMO-A).

[0402] (52) A Data Type Translator (DTT) as referred to in (6), whichdefines the data type dependencies for the Object Generator (IMO-G)according to the applications and database environment defined by theApplication/Database Definition Generator (ADG) described in(5 1).

[0403] (53) An Object Generator (IMO-G) as referred to in (53), whichautomates transformation of heterogeneous data sources and types intoIntelligent Molecular Object (IMO) data in real-time. Simultaneously,this object generator refreshes and updates the object state history.

[0404] (54) An Object Standardization Technique (IMO-S), which automatesthe normalization of data by calibration with standardized empiricalcriteria.

[0405] (55) An Application Framework (IMO-A) as referred to in (51),which provides integration and access protocols to heterogeneousapplications and databases on the object level.

[0406] (56) An Object Handler (IMO-H), which enables management ofIntelligent Molecular Object (IMO) data through integrated meta-data tagand pointers.

[0407] (57) An Intelligent Object Pool (IOP), comprising of subsets ofIntra-Pools (ipools) for Intelligent Molecular Object (IMO) dataarchitecture.

[0408] (58) A Set of Pool Boundary Protocol definitions, describingboundaries, integrity and persistence of Intelligent Molecular Object(IMO) relationships.

[0409] (59) A Set of Meta-data Query definitions, comprising of, but notrestricted to, interactive presorting and exclusion algorithms, objectclustering, a meta-data linking component, and object-to-objectinteraction definitions.

[0410] (60) A Set of Pool Content Access definitions, comprising of, butnot restricted to, object-to-analysis tools interactions, result mergingalgorithms, learning algorithms and a real-time answer generator.

[0411] (61) A Pool Boundary Protocol definition, comprising of an iPoolSecurity Authentication (iPSA) module to authenticate intra-pool datarequests according to user login and object data identification.

[0412] (62) A Pool Boundary Protocol definition, comprising of an iPoolAvailability Monitor (iPAM) and an iPool Exchange Protocol (iPEP), whichgovern intra-pool relationships.

[0413] (63) A Pool Boundary Protocol definition, comprising of an ObjectIntegrity Assessment (OIA) module to assess object integrity forsecurity and quality assurance/quality control.

[0414] (64) A Pool Boundary Protocol definition, comprising of an iPoolIntegrity Assessment (iPIA) module to assess data integrity within adefined intra-pool for security and quality assurance/quality control.

[0415] (65) A Meta-data Query definition, comprising of a Real-timeMeta-data Link (RML) component, which provides for rapid relevant dataaccess based on query parameters and global object meta-data index (MDX)content.

[0416] (66) A Meta-data Query definition, comprising of anObject-to-Object Query (OQM) component, which provides for rapid queryoptimization based on data object intercommunication regarding queryparameters and object meta-data index (MDX) content.

[0417] (67) A Meta-data Query definition, comprising of aniPool-to-iPool Query (PPQ) component, which provides for queryoptimization based on intra-pool data intercommunication regarding queryparameters and global object meta-data index (MDX) content containedwithin more than one intelligent object intra-pool (IOP).

[0418] (68) A Pool Content Access definition, comprising of an AggregateMeta-data Index Generator (aMDX), which provides for meta-data indexgeneration of aggregated intelligent molecular object meta-data, basedon query parameters.

[0419] (69) A Pool Content Access definition, comprising of an AggregateReal-time Significance Generator (aRSG), which provides for significancedetection of values located within the global data pool based on queryparameters and global object meta-data index (MDX) content.

[0420] (70) An iPool Content Order definition, comprising of an objectproperty-selective pre-sorting tool, the IMO Zoomer, which organizesmeta-data index based object relationships within individual iPools toallow for real-time result aggregation and real-time exclusion ofirrelevant object data layers.

[0421] Although the foregoing invention has been described in somedetail by way of illustration and example for purposes of clarity ofunderstanding, it will be readily apparent to those of ordinary skill inthe art in light of the teachings of this invention that certain changesand modifications may be made thereto without departing from the spiritor scope of the appended claims. All patents and publications referencedherein are hereby incorporated by reference.

We claim:
 1. A software architecture for an information technologyplatform, comprising of always-on and event-driven, engines, interfacesand processes and using intelligent molecular software data objects forinteractive data records.
 2. The architecture in claim 1, furthercomprising: a. an Intelligent Molecular Object (IMO), a versatile,data-enabling software object, which provides for real-time translation,integration, and object-to-object/object-to-analysis tools communicationat the object data level, to allow multidimensional,platform-independent complex queries in real-time; b. an IntelligentObject Handler (IOH), which provides the application framework and userinterface for IMO data, to allow for seamless integration of theirbenefits into legacy systems; and c. an Intelligent Object Pool (IOP),comprising one global virtual data pool comprised of IMO data, whichintegrates diverse data resources on any system or network to provideresult aggregation and instant answers across diversified data subsets.3. The architecture in claim 2, wherein the IMO is further comprised of:a. a unique identifier (UID), comprising a property pane layer createdat IMO generation, which provides typically a 10 byte, alphanumericunique identification on any system or network; b. an object accessmanager (OAM), a property pane layer which governs data security andaccess according to UID permissions; c. an object root router (ORR), aproperty pane layer which contains information to define the origin ofthe object within the system or network; d. an interactive contentrouter (ICR), a property pane layer which routes content and resultsinteractively across the system or network; e. a status managementcomponent (SMC), comprised of an object state engine and certaininterfaces, which monitors data integrity and command history inGLP/GMP-compliance via state history and governs table lookup actionsvia the ICR; f. a property pane controller (PPC), which controls theinitiation of IMO communication according to activation by claims 3 athrough 3 d, above; g. vector subsets (VSS) for automatic, dynamic, oruser-defined workspace definitions, which provide vectorized, directaddressing of data subsets for the ICR to minimize network traffic; h.meta-data indices (MDX), to provide efficient access via dynamicallyupdated meta-data description relevant to extant data queries anddefinitions; i. object pane descriptors (OPD), which provide informationabout each object property pane and their function as required fordirect communication with diversified applications and databases; j. aninterface for direct information interchange (DII), which provides theinterface to communication at the object level; k. an applicationtranslator link (ATL), which activates the OAM and ICR to determine theproperty panes for functional presentation and access within a givenapplication or database environment;
 1. an object graph preview (OGP)pane, comprising a limited resolution image and graphics viewer forquick graphical data review, particularly of image data and spectraldatasets; m. a raw data matrix (RDM), comprising a property pane whichprovides the full information subset for any data format or structure;and, n. matrix structure definitions (MSD), which allows for data fieldmapping and enables vector access to specific data fields.
 4. Thearchitecture in claim 2, wherein the IOH further comprises: a. a unifiedpresentation layer (UPL), which provides a web-enabled graphical userinterface (GUI) to integrate components and/or modules from diverseapplications, laboratory systems environments and to act as handler forIMO data; b. a user definition administration shell (UDA), which setsups and governs access privileges to individual IMO data at theuser-defined level and is accessible within heterogeneous networkenvironments; c. at least one engine for data object normalization andstandardization, image normalization and standardization, IMO datatranslation, distributed learning, and knowledge extraction; d. at leastone access interface to and in-between instruments, data andapplications, comprising interfaces which include, but are not limitedto, direct instrument acquisition and control, application translation,direct object query, result generation, and legacy synchronization; e. amaster query component (MQC), create complex, multidimensional queries,containing pre-defined, configurable subsets of forms commonly used, butnot restricted to, in diverse areas of Life Sciences; f. an IMOgenerator (IMO-G), an event-driven component to acquire data fromheterogeneous data resources, including from ongoing data acquisition,in real-time and transforms device outputs and heterogeneous data typesto IMO data; g. an IMO handler (IMO-H), which enables user management ofIMO data utilizing integrated meta-data tags and pointers; h. an IMOapplication framework (IMO-A), which provides integration and accessprotocols to heterogeneous applications and databases on the objectlevel; i. an application definition generator (ADG), which automates thequery and generation of application and defines computing environmentsfor the IMO data translation; j. at least one data type translator(DTT), which define the data type dependencies for the IMO-G accordingto the applications and database environments defined by the ADG; and k.an automated application assembly component (AAA), which provides forjust-in-time (JIT) module linking.
 5. The architecture in claim 2,wherein the IOP further comprises: a. sets of Intra-Pools (iPools),regulated by boundary protocols, which provide data subset managementand the define integrity and persistence of IMO relationships; b. iPoolsecurity authentication protocols (iPSA), which authenticates iPool datarequests according to user login and object data identification; c.iPool availability monitoring protocols (iPAM), which define the iPoolavailability and access requirements of diverse data subsets; d. iPoolexchange protocols (iPEP), which determine and govern iPool dataexchange protocols according to user-defined criteria; e. an objectintegrity assessment component (OIA), which assess object integrity forsecurity and QA/QC; f. sets of engines and interfaces to access andgenerate ranked results within the IOP, including but not limited to anintegrity assessment interface, a real-time meta-data linking interfaceand an iPool-to-iPool query interface; g. an iPool meta-data index(iMDX), which provides dynamic, automated, and user-defined meta-dataindices at the iPool level; h. an aggregate meta-data index (aMDX),which provides dynamic, automated, and user-defined meta-data indices atthe aggregate IMO level, inclusive of all relevant data resources; i. anobject-to-object query meta-data sorter (OQM), to generate temporarytables based on dynamic, automated, and user-defined meta-data indices;and j. an aggregate real-time significance generator (aRSG), whichprovides for significance detection of values based on query parameters,meta-data indices when relevant, and IMO data ranking.
 6. Thearchitecture in claim 4, wherein the engines further comprise: a. anobject state engine (OSE), which provides a continuously-running (alwayson) set of processes, which monitor and govern activities of IMO data,performing real-time recording, updating and logging functions inGLP/GMP-compliant format.
 7. The architecture in claim 4, wherein theengines further comprise: a. a set of IMO standardization techniques(IMO-S), comprising engines which provide algorithms for tracking,standardization and/or normalization of object data; b. an genericobject normalization engine (ONE), which extracts variable andnon-variable regions within any set of object data and generates aglobal standard to which all data can be referred; c. an engine forglobal image normalization (GIN), which extracts variable andnon-variable regions within any set of image data and generates a globalstandard to which all data can be referred; d. an object translationengine (OTE), which is comprised of methods and functions for real-timemeta-data extraction and table generation of raw data matrix, dataobject, data field, data structure, data functional information, datatype, database type, and application type definitions for the OPD; e. adistributed learning engine (DLE), which provides algorithms fordynamic, automated, and user-defined hypothesis generation utilizingglobal data resources; and f. a knowledge extraction engine (KEE), whichprovides algorithms for dynamic, automated, and user-definedsignificance discovery and report generation.
 8. The architecture inclaim 5, wherein the engines further comprise: a. a result aggregationengine (RAE), to validate, assemble, rank and tabulate results passedfrom the IOH and to generate output reports across diversified datasubsets.
 9. The architecture in claim 3, wherein the interfaces furthercomprise: a. a direct information interchange interface (DII), whichallows for rapid analysis and results aggregation by providing theinterface for object-to-object and object-to-analysis tools via suchrelated interfaces and engines including, but not limited to the OQI,OTE, and the DLE.
 10. The architecture in claim 4, wherein theinterfaces further comprise: a. a graphical user interface (GUI),utilizing web-enabling standards including but not limited to Java andXML; b. a direct instrument acquisition and control interface (DIAC),which provides bi-directional real-time communication between the IOH,the IMO and diverse instrumentation; c. an application translationinterface (ATI), to provide automated real-time detection of diversedata and applications and gate bi-directional access to the OTE, thusenabling functional, standardized integration of IMO data withinheterogeneous data and applications environments; d. an object queryinterface (OQI), comprising an interface for direct informationinterchange (DII) with IMO data, which initiates query analysis andresults aggregation; e. a result generation interface (RGI) ) to providevalidated, assembled, ranked and tabulated results to the RAE, thusenabling the generation of output reports across diversified datasubsets; and f. a legacy synchronization interface (LSI), to providepersistence and synchronization of offline legacy data.
 11. Thearchitecture in claim 4, wherein the interfaces further comprise: a. aniPool integrity assessment interface (iPIA), to asses data integritywithin a defined iPool for security and QA/QC; b. a real-time meta-datalink interface (RML), which provides for rapid relevant data accessbased on query parameters and MDX information; c. a pool-to-pool queryinterface (PPQ), which provides for query optimization based on queryparameters and relevant iPool data and meta-data intercommunication;and, d. an IMO Zoomer (IMO-Z), which defines proximity and functionalranking of individual IMO data within the IOP and enablesmultidimensional IMO data viewing to represent object relationshipswithin the pool and in relationship to other iPools.
 12. An Architectureusing interactive Objects for real-time, efficient, multidimensional,interdependent intelligent queries.
 13. An Intelligent Object comprisinga set of functional layers or panes.
 14. An information technologysystem, comprising: an Intelligent Molecular Object (IMO); anIntelligent Object Handler (IOH); and an Intelligent Object Pool (IOP);said IMO, IOH, and IOP being adapted to communicate and interoperatewith each other.
 15. The information technology system as in claim 14,wherein: said Intelligent Molecular Object (IMO) providing a versatile,data-enabling software object, which further provides for real-timetranslation, integration, and object-to-object/object-to-analysis toolscommunication at the object data level, to allow multidimensional,platform-independent complex queries in real-time; said IntelligentObject Handler (IOH) provides the application framework and userinterface for IMO data, to allow for seamless integration of theirbenefits into legacy systems; and said Intelligent Object Pool (IOP)comprising one global virtual data pool comprised of IMO data, whichintegrates diverse data resources on any system or network to provideresult aggregation and instant answers across diversified data subsets.16. The architecture in claim 14, wherein the IMO is further comprisedof: a unique identifier (UID), comprising a property pane layer createdat IMO generation, which provides typically a multi-byte, alphanumericunique identification on any system or network.
 17. The architecture inclaim 14, wherein the IMO is further comprised of: an object accessmanager (OAM), a component within a property pane layer which governsdata security and access according to UID permissions.
 18. Thearchitecture in claim 14, wherein the IMO is further comprised of: anobject root router (ORR), a component within a property pane layer whichcontains information to define the origin of the object within thesystem or network.
 19. The architecture in claim 14, wherein the IMO isfurther comprised of: an interactive content router (ICR), a componentwithin a property pane layer which routes content and resultsinteractively across the system or network.
 20. The architecture inclaim 14, wherein the IMO is further comprised of: a status managementcomponent (SMC), interacting with an object state engine and certaininterfaces, which monitors data integrity and command history inGLP/GMP-compliance via state history and governs table lookup actionsvia the ICR.
 21. The architecture in claim 14, wherein the IMO isfurther comprised of: a property pane controller (PPC), which controlsthe initiation of IMO communication according to an activation.
 22. Thearchitecture in claim 14, wherein the IMO is further comprised of:vector subsets (VSS) for automatic, dynamic, or user-defined workspacedefinitions, which provide vectorized, direct addressing of data subsetsfor the ICR to minimize network traffic.
 23. The architecture in claim14, wherein the IMO is further comprised of: meta-data indices (MDX), toprovide efficient access via dynamically updated meta-data descriptionrelevant to extant data queries and definitions.
 24. The architecture inclaim 14, wherein the IMO is further comprised of: object panedescriptors (OPD), which provide information about each object propertypane and their function as required for direct communication withdiversified applications and databases.
 25. The architecture in claim14, wherein the IMO is further comprised of: an object query interfacefor direct information interchange (DII), which provides the interfaceto communication at the object level.
 26. The architecture in claim 14,wherein the IMO is further comprised of: an application translator link(ATL), which activates the OAM and ICR to determine the property panesfor functional presentation and access within a given application ordatabase environment.
 27. The architecture in claim 14, wherein the IMOis further comprised of: an object graph preview (OGP) pane, comprisinga limited resolution image and graphics viewer for quick graphical datareview, particularly of image data and spectral datasets.
 28. Thearchitecture in claim 14, wherein the IMO is further comprised of: a rawdata matrix (RDM), comprising a property pane which provides the fullinformation subset for any data format or structure.
 29. Thearchitecture in claim 14, wherein the IMO is further comprised of:matrix structure definitions (MSD), which allows for data field mappingand enables vector access to specific data fields.